Search

Your search keyword '"Multiple view"' showing total 1,145 results
Start Over Descriptor "Multiple view"
1,145 results on '"Multiple view"'

1. A Brief Overview of the Development and Significance of Modern Scientific Medicine in China: Take Chinese Academy of Medical Science and Peking Union Medical College as an Example.

Author

Cui, Pu-An, Gong, Zhe-Xi, and He, Zhong

Subjects
*MEDICAL schools, *MEDICAL sciences, *CHINESE medicine, *WESTERN civilization, *TWENTIETH century
Abstract

Since the early 20th century, China has gradually established a clinical, educational, and research system centered around modern scientific medicine, which has now become the dominant force in China's medical and health system and services, with the construction and development of the Chinese Academy of Medical Sciences and Peking Union Medical College as the most prominent symbol. The scientific medicine in the new era requires close cooperation across multiple disciplines and fields to build a high-quality and efficient medical and health service system. It also involves combining the excellent traditional Chinese culture with Western medicine to explore a unique path of modern scientific medicine with Chinese characteristics. [ABSTRACT FROM AUTHOR]

Published
2024
Full Text
View/download PDF

2. WaRoNav: Warehouse Robot Navigation Based on Multi-view Visual-Inertial Fusion

Author

Zhang, Yinlong, Li, Bo, Liu, Yuanhao, Liang, Wei, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Liu, Qingshan, editor, Wang, Hanzi, editor, Ma, Zhanyu, editor, Zheng, Weishi, editor, Zha, Hongbin, editor, Chen, Xilin, editor, Wang, Liang, editor, and Ji, Rongrong, editor

Published
2024
Full Text
View/download PDF

3. GrapeMOTS: UAV vineyard dataset with MOTS grape bunch annotations recorded from multiple perspectives for enhanced object detection and tracking

Author

Mar Ariza-Sentís, Kaiwen Wang, Zhen Cao, Sergio Vélez, and João Valente

Subjects
Occlusion, UAV, Multiple view, Object detection and tracking, Precision viticulture, MOTS, Computer applications to medicine. Medical informatics, R858-859.7, Science (General), Q1-390
Abstract

Object Detection and Tracking have provided a valuable tool for many tasks, mostly time-consuming and prone-to-error jobs, including fruit counting while in the field, among others. Fruit counting can be a challenging assignment for humans due to the large quantity of fruit available, which turns it into a mentally-taxing operation. Hence, it is relevant to use technology to ease the task of farmers by implementing Object Detection and Tracking algorithms to facilitate fruit counting. However, those algorithms suffer undercounting due to occlusion, which means that the fruit is hidden behind a leaf or a branch, complicating the detection task. Consequently, gathering the datasets from multiple viewing angles is essential to boost the likelihood of recording the images and videos from the most visible point of view. Furthermore, the most critical open-source datasets do not include labels for certain fruits, such as grape bunches. This study aims to unravel the scarcity of public datasets, including labels, to train algorithms for grape bunch Detection and Tracking by considering multiple angles acquired with a UAV to overcome fruit occlusion challenges.

Published
2024
Full Text
View/download PDF

5. Container ISO Code Recognition System Using Multiple View Based on Google LSTM Tesseract

Author

Shithil, Shaekh Mohammad, Kamil, Ahmad Ridhwan Mohd, Tasnim, Sadat, Faudzi, Ahmad Athif Mohd, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, Kumar, Amit, editor, Zurada, Jacek M., editor, Gunjan, Vinit Kumar, editor, and Balasubramanian, Raman, editor

Published
2022
Full Text
View/download PDF

6. Swipe versus multiple view: a comprehensive analysis using eye-tracking to evaluate user interaction with web maps.

Author

Popelka, Stanislav, Burian, Jaroslav, and Beitlova, Marketa

Subjects
*EYE tracking, *INTERNET users, *MAPS, *MULTIPLE comparisons (Statistics), *GEOGRAPHERS
Abstract

The comparison of multiple maps is a common fundamental process used by geographers to explore the world. The most frequently applied interactive methods for the comparison of maps are multiple view and swipe. Swipe allows the user to interactively drag and overlap two different maps. Multiple view is based on the simultaneous side-by-side display of several maps. The current paper presents an analysis of the use of these two map comparison techniques in an Esri environment using an eye-tracking study which involved 25 participants. The participants completed two different tasks which compared land suitability using two or four maps. Based on an analysis of the recorded data, we compared the effectiveness of these methods through the accuracy of answers, the trial duration, and eye-tracking metrics of the individual compositional elements of the interactive maps. Cognitive processing was investigated through the analysis of dynamic areas of interest. This labor-intensive analysis yielded results which could be visualized using sequence charts. Based on these analyses, we concluded that the participants worked more effectively with multiple views, especially in comparing four maps. Working with swipe in the Esri environment is non-intuitive in comparisons of more than two maps. Many participants instead preferred simple toggling between layers instead of interactive swipe comparisons. However, when swipe was used to compare two maps, the method was more efficient, especially during cognitively demanding tasks. [ABSTRACT FROM AUTHOR]

Published
2022
Full Text
View/download PDF

7. A composite framework of deep multiple view human joints feature extraction and selection strategy with hybrid adaptive sunflower optimization‐whale optimization algorithm for human action recognition in video sequences.

Author

Rajappan, Rajitha Jasmine and Kondampatti Kandaswamy, Thyagharajan

Subjects
*FEATURE selection, *DEEP learning, *JOINTS (Anatomy), *FEATURE extraction, *HUMAN behavior, *PATTERN recognition systems, *MINKE whale
Abstract

In computer vision and pattern recognition field, video‐based human action recognition (HAR) is the most predominant research area. Object recognition is needed to recognize the subjects regarding video contents, which allows reactive enquiry in a large number of camera contents, mainly in security based platforms where there is a prevalent growth of closed circuit television cameras. Generally, object detectors that have high performance are trained on a large collection of public benchmarks. Identifying human activities from unconstrained videos is the primary challenging task. Further, the feature extraction and feature selection from these unconstrained videos is also considered as a challenging issue. For that, in this article a new composite framework of HAR model is constructed by introducing an efficient feature extraction and selection strategy. The proposed feature extraction model extracts multiple view features, human joints features based on the domain knowledge of the action and fuses them with deep high level features extracted by an improved fully resolution convolutional neural networks. Also, it optimizes the feature selection strategy using the hybrid whale optimization algorithm and adaptive sun flower optimization that maximizes the feature entropy, correlation. It minimizes the error rate for improving the recognition accuracy of the proposed composite framework. The proposed model is validated on four different datasets, namely, Olympics sports, Virat Release 2.0, HMDB51, and UCF 50 sports action dataset to prove its effectiveness. The simulation results show that the proposed composite framework outperforms all the existing human recognition model in terms of classification accuracy and detection rate. [ABSTRACT FROM AUTHOR]

Published
2022
Full Text
View/download PDF

8. Implementation of Multiple View Approach for Pose Estimation with an Eye-In-Hand Robotic System

Author

Li, Kai, Zhuang, Chungang, Wu, Jianhua, Xiong, Zhenhua, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Huang, YongAn, editor, Wu, Hao, editor, Liu, Honghai, editor, and Yin, Zhouping, editor

Published
2017
Full Text
View/download PDF

9. Cross-View Feature Hashing for Image Retrieval

Author

Wu, Wei, Li, Bin, Chen, Ling, Zhang, Chengqi, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Bailey, James, editor, Khan, Latifur, editor, Washio, Takashi, editor, Dobbie, Gill, editor, Huang, Joshua Zhexue, editor, and Wang, Ruili, editor

Published
2016
Full Text
View/download PDF

10. A Concise Yet Effective Model for Non-Aligned Incomplete Multi-View and Missing Multi-Label Learning

Author

Songcan Chen and Xiang Li

Subjects
FOS: Computer and information sciences, Computer Science - Machine Learning, Information privacy, Exploit, Computer science, Computer Vision and Pattern Recognition (cs.CV), Computer Science - Computer Vision and Pattern Recognition, Multi label learning, Space (commercial competition), Machine learning, computer.software_genre, Machine Learning (cs.LG), Machine Learning, Artificial Intelligence, Time complexity, Models, Statistical, Efficient algorithm, business.industry, Applied Mathematics, Model selection, Computational Theory and Mathematics, Supervised Machine Learning, Computer Vision and Pattern Recognition, Artificial intelligence, Multiple view, business, computer, Algorithms, Software
Abstract

In reality, learning from multi-view multi-label data inevitably confronts three challenges: missing labels, incomplete views, and non-aligned views. Existing methods mainly concern the first two and commonly need multiple assumptions to attack them, making even state-of-the-arts involve at least two explicit hyper-parameters such that model selection is quite difficult. More roughly, they will fail in handling the third challenge, let alone addressing the three jointly. In this paper, we aim at meeting these under the least assumption by building a concise yet effective model with just one hyper-parameter. To ease insufficiency of available labels, we exploit not only the consensus of multiple views but also the global and local structures hidden among multiple labels. Specifically, we introduce an indicator matrix to tackle the first two challenges in a regression form while aligning the same individual labels and all labels of different views in a common label space to battle the third challenge. In aligning, we characterize the global and local structures of multiple labels to be high-rank and low-rank, respectively. Subsequently, an efficient algorithm with linear time complexity in the number of samples is established. Finally, even without view-alignment, our method substantially outperforms state-of-the-arts with view-alignment on five real datasets., 15 pages, 7 figures

Published
2022
Full Text
View/download PDF

11. GCMVF-AGV : Globally Consistent Multiview Visual-Inertial Fusion for AGV Navigation in Digital Workshops

Author

Zhang, Yinlong, Li, Bo, Sun, Shijie, Liu, Yuanhao, Liang, Wei, Xia, Xiaofang, Pang, Zhibo, Zhang, Yinlong, Li, Bo, Sun, Shijie, Liu, Yuanhao, Liang, Wei, Xia, Xiaofang, and Pang, Zhibo

Abstract

An accurate and globally consistent navigation system is crucial for estimating the positions and attitudes of automated guided vehicles (AGVs) in digital workshops. A promising navigation technology for this purpose is tightly coupled visual-inertial fusion, which offers advantages such as quick response (QR), absolute scale, and accuracy. However, existing visual-inertial fusion systems have limitations, including long-term drift, tracking failures in textureless or poorly illuminated environments, and a lack of absolute references. To create a reliable and consistent AGV navigation framework and correct for long-term drift, we have designed a novel framework, globally consistent multiview visual-inertial fusion for AGV navigation (GCMVF-AGV). This framework uses a downward-looking QR vision sensor and a forward-looking visual-inertial sensor together to estimate AGV poses in real time. The downward camera provides absolute AGV positions and attitudes with reference to the global workshop frame. Furthermore, long-term visual-inertial drift, inertial biases, and velocities are periodically compensated between spatial intervals of QR codes by minimizing visual-inertial residuals with the rigid constraints of absolute poses estimated from the downward visual measurements. We have evaluated the proposed method on the developed AGV navigation platform, and experimental results demonstrate the position and attitude errors of less than 0.05 m and 2 degrees, respectively., QC 20231130

Published
2023
Full Text
View/download PDF

12. GrapeMOTS: UAV vineyard dataset with MOTS grape bunch annotations recorded from multiple perspectives for enhanced object detection and tracking.

Author

Ariza-Sentís M, Wang K, Cao Z, Vélez S, and Valente J

Abstract

Object Detection and Tracking have provided a valuable tool for many tasks, mostly time-consuming and prone-to-error jobs, including fruit counting while in the field, among others. Fruit counting can be a challenging assignment for humans due to the large quantity of fruit available, which turns it into a mentally-taxing operation. Hence, it is relevant to use technology to ease the task of farmers by implementing Object Detection and Tracking algorithms to facilitate fruit counting. However, those algorithms suffer undercounting due to occlusion, which means that the fruit is hidden behind a leaf or a branch, complicating the detection task. Consequently, gathering the datasets from multiple viewing angles is essential to boost the likelihood of recording the images and videos from the most visible point of view. Furthermore, the most critical open-source datasets do not include labels for certain fruits, such as grape bunches. This study aims to unravel the scarcity of public datasets, including labels, to train algorithms for grape bunch Detection and Tracking by considering multiple angles acquired with a UAV to overcome fruit occlusion challenges., (© 2024 The Author(s).)

Published
2024
Full Text
View/download PDF

14. Multiview Depth Parameterisation with Second Order Regularisation

Author

Schroers, Christopher, Hafner, David, Weickert, Joachim, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Aujol, Jean-François, editor, Nikolova, Mila, editor, and Papadakis, Nicolas, editor

Published
2015
Full Text
View/download PDF

17. View-Constrained Latent Variable Model for Multi-view Facial Expression Classification

Author

Eleftheriadis, Stefanos, Rudovic, Ognjen, Pantic, Maja, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Kobsa, Alfred, Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Bebis, George, editor, Boyle, Richard, editor, Parvin, Bahram, editor, Koracin, Darko, editor, McMahan, Ryan, editor, Jerald, Jason, editor, Zhang, Hui, editor, Drucker, Steven M., editor, Kambhamettu, Chandra, editor, El Choubassi, Maha, editor, Deng, Zhigang, editor, and Carlson, Mark, editor

Published
2014
Full Text
View/download PDF

18. Self-explanatory Sparse Representation for Image Classification

Author

Liu, Bao-Di, Wang, Yu-Xiong, Shen, Bin, Zhang, Yu-Jin, Hebert, Martial, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Kobsa, Alfred, Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Fleet, David, editor, Pajdla, Tomas, editor, Schiele, Bernt, editor, and Tuytelaars, Tinne, editor

Published
2014
Full Text
View/download PDF

19. Affine Subspace Representation for Feature Description

Author

Wang, Zhenhua, Fan, Bin, Wu, Fuchao, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Kobsa, Alfred, Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Fleet, David, editor, Pajdla, Tomas, editor, Schiele, Bernt, editor, and Tuytelaars, Tinne, editor

Published
2014
Full Text
View/download PDF

20. Interaction in the Visualization of Multivariate Networks

Author

Wybrow, Michael, Elmqvist, Niklas, Fekete, Jean-Daniel, von Landesberger, Tatiana, van Wijk, Jarke J., Zimmer, Björn, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Kobsa, Alfred, Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Kerren, Andreas, editor, Purchase, Helen C., editor, and Ward, Matthew O., editor

Published
2014
Full Text
View/download PDF

21. Tracking People with Active Cameras

Author

Yildiz, Alparslan, Takemura, Noriko, Iwai, Yoshio, Sato, Kosuke, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, and Kurosu, Masaaki, editor

Published
2013
Full Text
View/download PDF

22. Co-regularized PLSA for Multi-view Clustering

Author

Jiang, Yu, Liu, Jing, Li, Zechao, Li, Peng, Lu, Hanqing, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Lee, Kyoung Mu, editor, Matsushita, Yasuyuki, editor, Rehg, James M., editor, and Hu, Zhanyi, editor

Published
2013
Full Text
View/download PDF

23. Fast Multi-View Semi-Supervised Learning With Learned Graph

Author

Feiping Nie, Qianyao Qiang, Fei Wang, and Bin Zhang

Subjects
Computer Science::Machine Learning, Computational complexity theory, Computer science, business.industry, Semi-supervised learning, Machine learning, computer.software_genre, Graph, Computer Science Applications, Effective algorithm, Computational Theory and Mathematics, Task analysis, Bipartite graph, Artificial intelligence, Multiple view, business, computer, Information Systems, Utilization
Abstract

Multi-view semi-supervised learning (SSL) has attracted great attention due to its effectiveness in information utilization of multiple views and labeled and unlabeled data to solve practical problems. However, most existing methods exhibit high computational complexity. Effective integration of the information on different views to achieve enhanced performance remains a challenging task. In this study, we combine an anchor-based approach with multi-view semi-supervised learning to address these problems. A novel multi-view SSL method called fast multi-view SSL (FMSSL) based on learned graph is proposed. Starting from the affinity graphs constructed by using an anchor-based strategy, FMSSL learns an optimal multi-view consensus graph by using feature and label information. The learned graph can jointly consider the relation of multiple views to approximate the manifold structure. The learned graph is then introduced into the SSL model as the weight matrix of a bipartite graph to simultaneously perform separate classification on the original samples and anchors. Accordingly, multi-view SSL can be efficiently performed, and the computational complexity can be significantly reduced. We propose an effective algorithm to optimize the objective function. Extensive experimental results on different real-world datasets demonstrate the effectiveness and efficiency of the proposed algorithm.

Published
2022
Full Text
View/download PDF

24. Learning the Global Descriptor for 3-D Object Recognition Based on Multiple Views Decomposition

Author

Thomas H. Li, Jingjia Huang, Shan Liu, Ge Li, and Wei Yan

Subjects
Computer science, business.industry, Signal Processing, Media Technology, Decomposition (computer science), Cognitive neuroscience of visual object recognition, Pattern recognition, Artificial intelligence, Electrical and Electronic Engineering, Multiple view, business, Computer Science Applications
Published
2022
Full Text
View/download PDF

25. iModel: Interactive Co-segmentation for Object of Interest 3D Modeling

Author

Kowdle, Adarsh, Batra, Dhruv, Chen, Wen-Chao, Chen, Tsuhan, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, and Kutulakos, Kiriakos N., editor

Published
2012
Full Text
View/download PDF

26. InShape: In-Situ Shape-Based Interactive Multiple-View Exploration of Diffusion MRI Visualizations

Author

Cai, Haipeng, Chen, Jian, Auchus, Alexander P., Correia, Stephen, Laidlaw, David H., Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Bebis, George, editor, Boyle, Richard, editor, Parvin, Bahram, editor, Koracin, Darko, editor, Fowlkes, Charless, editor, Wang, Sen, editor, Choi, Min-Hyung, editor, Mantler, Stephan, editor, Schulze, Jürgen, editor, Acevedo, Daniel, editor, Mueller, Klaus, editor, and Papka, Michael, editor

Published
2012
Full Text
View/download PDF

27. An Application of the Self-Organizing Map to Multiple View Unsupervised Learning

Author

Gałkowski, Tomasz, Starczewski, Artur, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Goebel, Randy, editor, Siekmann, Jörg, editor, Wahlster, Wolfgang, editor, Rutkowski, Leszek, editor, Korytkowski, Marcin, editor, Scherer, Rafał, editor, Tadeusiewicz, Ryszard, editor, Zadeh, Lotfi A., editor, and Zurada, Jacek M., editor

Published
2012
Full Text
View/download PDF

28. Bladder Cancer: Update on Risk Factors, Molecular and Ultrastructural Patterns

Author

Cecil E Kirkland, Siva G Somasundaram, V.V. Pechnikova, Olga I Patsap, Olesya A. Vasyukova, Ozal Beylerli, Emma P. Akopyan, Akhmed M Pshikhachev, Liudmila M. Mikhaleva, Magomed A Gusniev, Konstantin A Rogov, and Gjumrakch Aliev

Subjects
medicine.medical_specialty, MEDLINE, Bioinformatics, Biochemistry, Risk Factors, PD-L1, Drug Discovery, Epidemiology, Humans, Medicine, Neoplasm Invasiveness, Pharmacology, Bladder cancer, biology, Mechanism (biology), business.industry, Organic Chemistry, Limiting, medicine.disease, Urinary Bladder Neoplasms, Tumor morphology, Mutation, biology.protein, Molecular Medicine, business, Multiple view, Biomarkers
Abstract

Objective: The molecular mechanisms of bladder cancer development and progression are not clear. Bladder cancer is an important focus for epidemiological studies and understanding clinical implications. Goal: The primary aim of prevention is achieved by limiting exposure to non-genetic risk factors such as smoking, diet, arsenic in drinking water, or aromatic amines at work or elsewhere. Current therapies for bladder cancer are affected by tumor morphology and associated acquired genetic mutations. Methods: A literature search was performed using PubMed, Scopus, ResearchGate, Google, MEDLINE, and ScienceDirect databases to find studies of bladder cancer published between 1984 and early 2020. The focus was articles that address epidemiological risk factors and underlying pathophysiological mechanism. Articles were selected that enabled our review of these factors as well as molecular and structural patterns. Results: There are multiple views of bladder cancer. The literature offers a number of novel insights regarding the development and progression of bladder cancer and possible biomarkers that may be useful in clinical and diagnostic practice. Conclusion: There are several molecular pathways associated with bladder cancer that are frequently updated. In addition, genetic subtypes of bladder tumors are not distinguished clearly that requires future more detailed analysis.

Published
2021
Full Text
View/download PDF

29. MVSN: A Multi-view stack network for human parsing

Author

Ge Lin, Minshi Chen, Fan Zhou, Enbo Huang, and Zhuo Su

Subjects
Parsing, Channel (digital image), Computer science, Cognitive Neuroscience, computer.software_genre, Computer Science Applications, Image (mathematics), Global information, Task (computing), Stack (abstract data type), Artificial Intelligence, Data mining, Multiple view, computer, Prior information
Abstract

The human parsing task is dedicated to allocating pixel-level fine-grained semantic labels. However, recent solutions are limited to fully utilize the prior information (poses and edges) and the potential information of the image data, remaining problems with ambiguous boundaries, incomplete human parts, and redundant labels. To solve the above problems, we propose a novel Multi-view Stack Network (MVSN), which is constructed by three stacks with multiple views of features included parts, edges, and pre-segmentation. Meanwhile, a channel correlator is developed to acquire the correlation between local and global information better. Comprehensive experiments and corresponding results on three public datasets show that the proposed MVSN performs favorably against the state-of-the-art methods.

Published
2021
Full Text
View/download PDF

30. Weighted multi-view common subspace learning method

Author

Xiaoqing Gong, Mei Shi, Xiaoxia Liu, Zhihui Li, Jun Guo, and Jing An

Subjects
Computer science, business.industry, Pattern recognition, Discriminative model, Artificial Intelligence, Scatter matrix, Signal Processing, Metric (mathematics), Learning methods, Computer Vision and Pattern Recognition, Artificial intelligence, Projection (set theory), Multiple view, business, Software, Subspace topology
Abstract

How to use multi-view data effectively has become one of the challenging problems in the computer vision community. The existing multi-view learning methods are mainly based on common subspace learning which aim to explore the discriminative information between multi-view data and find its potential common subspace. Most of the existing multi-view subspace learning methods rely on the within-class scatter matrix and between-class scatter matrix while capturing the discriminative information of multiple views. However, these methods just roughly minimize the within-class distance and maximize the between-class distance, and do not make full use of the intra-view and inter-view information. To address this problem, we propose a weighted common subspace learning method, which can effectively adjust the contribution ratio of between-class and within-class information through a weighted parameter, so that an optimized common subspace can be obtained. And we use the maximum scatter difference criterion as the metric of inter-view and intra-view after projection. Extensive experiments on the public data sets show the superiority of this method.

Published
2021
Full Text
View/download PDF

32. View Construction for Multi-view Semi-supervised Learning

Author

Sun, Shiliang, Jin, Feng, Tu, Wenting, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Liu, Derong, editor, Zhang, Huaguang, editor, Polycarpou, Marios, editor, Alippi, Cesare, editor, and He, Haibo, editor

Published
2011
Full Text
View/download PDF

36. Multi-view Modeling to Support Embedded Systems Engineering in SysML

Author

Shah, Aditya A., Kerzhner, Aleksandr A., Schaefer, Dirk, Paredis, Christiaan J. J., Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Engels, Gregor, editor, Lewerentz, Claus, editor, Schäfer, Wilhelm, editor, Schürr, Andy, editor, and Westfechtel, Bernhard, editor

Published
2010
Full Text
View/download PDF

37. Integrating Multiple Uncalibrated Views for Human 3D Pose Estimation

Author

Wang, Zibin, Chung, Ronald, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Bebis, George, editor, Boyle, Richard, editor, Parvin, Bahram, editor, Koracin, Darko, editor, Chung, Ronald, editor, Hammound, Riad, editor, Hussain, Muhammad, editor, Kar-Han, Tan, editor, Crawfis, Roger, editor, Thalmann, Daniel, editor, Kao, David, editor, and Avila, Lisa, editor

Published
2010
Full Text
View/download PDF

38. Multiple View Reconstruction of a Quadric of Revolution from Its Occluding Contours

Author

Gurdjos, Pierre, Charvillat, Vincent, Morin, Géraldine, Guénard, Jérôme, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Zha, Hongbin, editor, Taniguchi, Rin-ichiro, editor, and Maybank, Stephen, editor

Published
2010
Full Text
View/download PDF

39. Robust flow-guided neural prediction for sketch-based freeform surface modeling.

Author

Li, Changjian, Pan, Hao, Liu, Yang, Tong, Xin, Sheffer, Alla, and Wang, Wenping

Subjects
ARTIFICIAL neural networks, ROBUST control, ALGORITHMS, DEEP learning, IMAGE reconstruction
Abstract

Sketching provides an intuitive user interface for communicating free form shapes. While human observers can easily envision the shapes they intend to communicate, replicating this process algorithmically requires resolving numerous ambiguities. Existing sketch-based modeling methods resolve these ambiguities by either relying on expensive user annotations or by restricting the modeled shapes to specific narrow categories. We present an approach for modeling generic freeform 3D surfaces from sparse, expressive 2D sketches that overcomes both limitations by incorporating convolution neural networks (CNN) into the sketch processing workflow. Given a 2D sketch of a 3D surface, we use CNNs to infer the depth and normal maps representing the surface. To combat ambiguity we introduce an intermediate CNN layer that models the dense curvature direction, or flow, field of the surface, and produce an additional output confidence map along with depth and normal. The flow field guides our subsequent surface reconstruction for improved regularity; the confidence map trained unsupervised measures ambiguity and provides a robust estimator for data fitting. To reduce ambiguities in input sketches users can refine their input by providing optional depth values at sparse points and curvature hints for strokes. Our CNN is trained on a large dataset generated by rendering sketches of various 3D shapes using non-photo-realistic line rendering (NPR) method that mimics human sketching of free-form shapes. We use the CNN model to process both single- and multi-view sketches. Using our multi-view framework users progressively complete the shape by sketching in different views, generating complete closed shapes. For each new view, the modeling is assisted by partial sketches and depth cues provided by surfaces generated in earlier views. The partial surfaces are fused into a complete shape using predicted confidence levels as weights. We validate our approach, compare it with previous methods and alternative structures, and evaluate its performance with various modeling tasks. The results demonstrate our method is a new approach for efficiently modeling freeform shapes with succinct but expressive 2D sketches. [ABSTRACT FROM AUTHOR]

Published
2018
Full Text
View/download PDF

41. Domain Specific Intended Use Evaluation Method: Intrusion Detection Specific Intended Use Evaluation Method

Author

Park, Albert, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Park, Jong Hyuk, editor, Chen, Hsiao-Hwa, editor, Atiquzzaman, Mohammed, editor, Lee, Changhoon, editor, Kim, Tai-hoon, editor, and Yeo, Sang-Soo, editor

Published
2009
Full Text
View/download PDF

42. Comparison of Multiple View Strategies to Reduce False Positives in Breast Imaging

Author

Teubl, Joerg, Bischof, Horst, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, and Krupinski, Elizabeth A., editor

Published
2008
Full Text
View/download PDF

43. A framework for uncertainty-aware visual analytics of proteins

Author

Robin Georg Claus Maack, Christina Gillmann, Hans Hagen, Thomas Wischgoll, and Michael L. Raymer

Subjects
Visual analytics, business.industry, Computer science, Computation, General Engineering, 020207 software engineering, 02 engineering and technology, computer.file_format, ENCODE, Machine learning, computer.software_genre, Computer Graphics and Computer-Aided Design, Visualization, Human-Computer Interaction, Atom (standard), 0202 electrical engineering, electronic engineering, information engineering, 020201 artificial intelligence & image processing, Artificial intelligence, Multiple view, Representation (mathematics), business, computer, User feedback
Abstract

Due to the limitations of existing experimental methods for capturing stereochemical molecular data, there usually is an inherent level of uncertainty present in models describing the conformation of macromolecules. This uncertainty can originate from various sources and can have a significant effect on algorithms and decisions based upon such models. Incorporating uncertainty in state-of-the-art visualization approaches for molecular data is an important issue to ensure that scientists analyzing the data are aware of the inherent uncertainty present in the representation of the molecular data. In this work, we introduce a framework that allows biochemists to explore molecular data in a familiar environment while including uncertainty information within the visualizations. Our framework is based on an anisotropic description of proteins that can be propagated along with required computations, providing multiple views that extend prominent visualization approaches to visually encode uncertainty of atom positions, allowing interactive exploration. We show the effectiveness of our approach by applying it to multiple real-world datasets and gathering user feedback.

Published
2021
Full Text
View/download PDF

45. Structure Restriction for Tracking Through Multiple Views and Occlusions

Author

Martínez, B., Pérez, A., Ferraz, L., Binefa, X., Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Rangan, C. Pandu, editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Martí, Joan, editor, Benedí, José Miguel, editor, Mendonça, Ana Maria, editor, and Serrat, Joan, editor

Published
2007
Full Text
View/download PDF

46. Visual Representations

Author

Görg, Carsten, Pohl, Mathias, Qeli, Ermir, Xu, Kai, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Kerren, Andreas, editor, Ebert, Achim, editor, and Meyer, Jörg, editor

Published
2007
Full Text
View/download PDF

47. Real-Time and Markerless 3D Human Motion Capture Using Multiple Views

Author

Michoud, Brice, Guillou, Erwan, Bouakaz, Saïda, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Elgammal, Ahmed, editor, Rosenhahn, Bodo, editor, and Klette, Reinhard, editor

Published
2007
Full Text
View/download PDF

48. A left Atrial Mass After COVID-19 and Cardiac Surgery

Author

Thushara Dharshana Munasinghe and Madan Mohan Maddali

Subjects
2019-20 coronavirus outbreak, medicine.medical_specialty, Heart Diseases, Coronavirus disease 2019 (COVID-19), Heart Atria / diagnostic imaging, law.invention, Left atrial, law, Internal medicine, Cardiopulmonary bypass, medicine, Humans, Heart Atria, Cardiac Surgical Procedures, Left atrial mass, Diagnostic Dilemma, Heart diseases/surgery, SARS-CoV-2, business.industry, Infant, COVID-19, Invagination, Cardiac surgery, Anesthesiology and Pain Medicine, Cardiology, Cardiology and Cardiovascular Medicine, Multiple view, business, Echocardiography, Transesophageal, Intraoperative Care / methods
Abstract

Highlights When a new left atrial mass is encountered following open-heart surgery, it is important to be aware of the possibility of a left atrial invagination prior to resorting to drastic measures especially in the critical period after separation from cardiopulmonary bypass. Intraoperative transesophageal echocardiography is of immense value and the mass has to be evaluated in multiple views before arriving at a definitive diagnosis.

Published
2022
Full Text
View/download PDF

50. 3D and Texture Modelling of Precolombian Objects

Author

Hernández, Jorge, Prieto, Flavio, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Dough, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Bebis, George, editor, Boyle, Richard, editor, Parvin, Bahram, editor, Koracin, Darko, editor, Remagnino, Paolo, editor, Nefian, Ara, editor, Meenakshisundaram, Gopi, editor, Pascucci, Valerio, editor, Zara, Jiri, editor, Molineros, Jose, editor, Theisel, Holger, editor, and Malzbender, Tom, editor

Published
2006
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results