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447 results on '"Plaza, Javier"'

3. Substance use, mental health and dual disorders on pregnancy: Results of prevalence and treatment rates in a developed country/Salud mental, abuso de sustancias y trastornos duales en el embarazo: Tasas de prevalencia y tratamiento en un pais desarrollado

Author

Camacho, Rodrigo Carmona, Carpintero, Nayara Lopez, Barrigon, Maria Luisa, Nogales, Cristina Ruiz, Menendez, Ines, Alonso, Montserrat Sanchez, Canizares, Irene Caro, Aguado, Juan Jose Hernandez, Cook, Benjamin Le, Alegria, Margarita, Cornudella, Ricardo Saviron, Plaza, Javier, and Baca-Garcia, Enrique

Published
2022

10. Adaptive Deep Pyramid Matching for Remote Sensing Scene Classification

Author

Liu, Qingshan, Hang, Renlong, Song, Huihui, Zhu, Fuping, Plaza, Javier, and Plaza, Antonio

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Convolutional neural networks (CNNs) have attracted increasing attention in the remote sensing community. Most CNNs only take the last fully-connected layers as features for the classification of remotely sensed images, discarding the other convolutional layer features which may also be helpful for classification purposes. In this paper, we propose a new adaptive deep pyramid matching (ADPM) model that takes advantage of the features from all of the convolutional layers for remote sensing image classification. To this end, the optimal fusing weights for different convolutional layers are learned from the data itself. In remotely sensed scenes, the objects of interest exhibit different scales in distinct scenes, and even a single scene may contain objects with different sizes. To address this issue, we select the CNN with spatial pyramid pooling (SPP-net) as the basic deep network, and further construct a multi-scale ADPM model to learn complementary information from multi-scale images. Our experiments have been conducted using two widely used remote sensing image databases, and the results show that the proposed method significantly improves the performance when compared to other state-of-the-art methods.

Published
2016

21. Facilitators of and Barriers to Model School Psychological Services

Author

Castillo, Jose M., Arroyo-Plaza, Javier, Tan, Sim Yin, Sabnis, Sujay, and Mattison, Amira

Abstract

This study examined facilitators of and barriers to comprehensive and integrated services. A national sample of 267 full-time practicing school psychologists who were Regular Members or Early Career Members of the National Association of School Psychologists participated. We administered a survey to participants that measured the extent to which they engaged in comprehensive and integrated services and the top facilitators of and barriers to those services using web-based survey procedures. Results indicated that the majority of facilitators identified ("Personal Attributes," "Stakeholder Involvement," "Resources and Support," "School-Specific Variables," "Contextual Variables") predicted greater levels of comprehensive and integrated service delivery. Identified barriers--which often reflected the opposite condition of the facilitators--predicted lower levels of service delivery in some instances; however, they predicted services less often than did facilitators. Implications for research focused on better understanding factors that impact service delivery and on processes for facilitating increased comprehensive and integrated service delivery are discussed. Additionally, implications for practice include the assessment of facilitators and barriers, the use of data to plan for the delivery of comprehensive and integrated services, and advocacy for systems change.

Published
2017
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29. Cloud-Edge Selective Background Energy Constrained Filter for Real-Time Hyperspectral Target Detection

Author

Wang, Yunchang, Sun, Jin, Wei, Zhihui, Plaza, Javier, Plaza, Antonio, and Wu, Zebin

Abstract

Constrained by the performance of edge devices and real time (RT) processing technology, the existing hyperspectral target detection algorithms often struggle to rapidly distinguish targets from complex background pixels during real-time detection. To address this issue, this article proposes a new real-time cloud-edge selective background energy constrained (CE-SBEC) hyperspectral target detection algorithm. This algorithm aims to obtain detection results in real-time after capturing new data. Moreover, it conducts in-depth analysis based on existing detection results and updates the algorithm’s internal data to enhance its capabilities in terms of global background annihilation (GBA) and complex background suppression (CBS). Consequently, it improves the accuracy of subsequent real-time detection results. To enhance the resource utilization, this article deploys various task nodes of the algorithm separately on both the cloud and the edge, enabling collaborative execution of the CE-SBEC algorithm. In our context, edge devices are airborne equipment designed for the rapid acquisition and processing of data at the site of data collection, while cloud computing devices refer to high-performance computing clusters situated at a significant distance from the data collection site. Experimental results demonstrate that compared with existing detection algorithms, our newly proposed method achieves more accurate detection results while ensuring real-time performance.

Published
2024
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44. AMEEPAR: Parallel Morphological Algorithm for Hyperspectral Image Classification on Heterogeneous Networks of Workstations

Author

Plaza, Antonio, Plaza, Javier, Valencia, David, 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, Alexandrov, Vassil N., editor, van Albada, Geert Dick, editor, Sloot, Peter M. A., editor, and Dongarra, Jack, editor

Published
2006
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