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2,419 results on '"Popescu, Dan"'

1. Decision Fusion-Based System for Automatic Face Emotions Recognition

Author

Ichim, Loretta, Dinu, Silviu, Popescu, Dan, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, and Arai, Kohei, editor

Published
2024
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2. A Rare Cause of Urinary Incontinence: Vesicouterine Fistula?A Case Report

Author

Radu Viorel Dragos, Costache Radu Cristian, Onofriescu Mircea, Morosanu Corneliu, Onofrei Pavel, Bobeica Razvan Lucian, Tanasa Vasilache Ingrid, Tanase Adina, and Popescu Dan

Subjects
vesicouterine fistula, urinary incontinence, cesarean section, Gynecology and obstetrics, RG1-991, Public aspects of medicine, RA1-1270
Abstract

Vesicouterine fistula is a rare complication occurring mainly after cesarean sections. We present here a particular case of vesicouterine fistula (VUF) whose only symptom was urinary incontinence. We describe the diagnostic methods used and the surgical treatment used to resolve the case. A 30-year-old woman presented to the gynecology clinic with urinary incontinence that occurred 5 days postoperatively after a cesarean section. The diagnosis was made on the basis of computed tomography and cystoscopy. Treatment was surgical and consisted of excision of the fistula and suturing of the bladder and uterine wall, without interposition of the omentum. Postoperative evolution was uneventful. When the urethral catheter was removed on the 14th postoperative day, the patient presented spontaneous micturition without vaginal urine leakage. In the context of urinary incontinence after cesarean section, although it is a rare complication, we must consider the occurrence of a VUF.

Published
2024
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3. Halyomorpha Halys Detection in Orchard from UAV Images Using Convolutional Neural Networks

Author

Dinca, Alexandru, Popescu, Dan, Pinotti, Cristina Maria, Ichim, Loretta, Palazzetti, Lorenzo, Angelescu, Nicoleta, 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, Rojas, Ignacio, editor, Joya, Gonzalo, editor, and Catala, Andreu, editor

Published
2023
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4. Identification of Benign Tumor Masses Using Deep Learning Techniques Based on Semantic Segmentation

Author

El-Khatib, Mohamed, Teodor, Oana Mihaela, Popescu, Dan, Ichim, Loretta, 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, Rojas, Ignacio, editor, Joya, Gonzalo, editor, and Catala, Andreu, editor

Published
2023
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5. LASSNet: A Four Steps Deep Neural Network for Left Atrial Segmentation and Scar Quantification

Author

Lefebvre, Arthur L., Yamamoto, Carolyna A. P., Shade, Julie K., Bradley, Ryan P., Yu, Rebecca A., Ali, Rheeda L., Popescu, Dan M., Prakosa, Adityo, Kholmovski, Eugene G., Trayanova, Natalia A., 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, Zhuang, Xiahai, editor, Li, Lei, editor, Wang, Sihan, editor, and Wu, Fuping, editor

Published
2023
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6. Halyomorpha Halys Detection Using Efficient Neural Networks

Author

Dinca, Alexandru, Angelescu, Nicoleta, Ichim, Loretta, Popescu, Dan, 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, Tanveer, Mohammad, editor, Agarwal, Sonali, editor, Ozawa, Seiichi, editor, Ekbal, Asif, editor, and Jatowt, Adam, editor

Published
2023
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7. Anatomically-Informed Deep Learning on Contrast-Enhanced Cardiac MRI for Scar Segmentation and Clinical Feature Extraction

Author

Abramson, Haley G., Popescu, Dan M., Yu, Rebecca, Lai, Changxin, Shade, Julie K., Wu, Katherine C., Maggioni, Mauro, and Trayanova, Natalia A.

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition
Abstract

Visualizing disease-induced scarring and fibrosis in the heart on cardiac magnetic resonance (CMR) imaging with contrast enhancement (LGE) is paramount in characterizing disease progression and quantifying pathophysiological substrates of arrhythmias. However, segmentation and scar/fibrosis identification from LGE-CMR is an intensive manual process prone to large inter-observer variability. Here, we present a novel fully-automated anatomically-informed deep learning solution for left ventricle (LV) and scar/fibrosis segmentation and clinical feature extraction from LGE-CMR. The technology involves three cascading convolutional neural networks that segment myocardium and scar/fibrosis from raw LGE-CMR images and constrain these segmentations within anatomical guidelines, thus facilitating seamless derivation of clinically-significant parameters. In addition to available LGE-CMR images, training used "LGE-like" synthetically enhanced cine scans. Results show excellent agreement with those of trained experts in terms of segmentation (balanced accuracy of $96\%$ and $75\%$ for LV and scar segmentation), clinical features ($2\%$ difference in mean scar-to-LV wall volume fraction), and anatomical fidelity. Our segmentation technology is extendable to other computer vision medical applications and to problems requiring guidelines adherence of predicted outputs., Comment: Haley G. Abramson and Dan M. Popescu contributed equally to this work

Published
2020

11. IoT-Enabled Distributed Data Processing for Precision Agriculture

Author

Stamatescu, Grigore, Dragana, Cristian, Stamatescu, Iulia, Ichim, Loretta, and Popescu, Dan

Subjects
Electrical Engineering and Systems Science - Signal Processing
Abstract

Large scale monitoring systems, enabled by the emergence of networked embedded sensing devices, offer the opportunity of fine grained online spatio-temporal collection, communication and analysis of physical parameters. Various applications have been proposed and validated so far for environmental monitoring, security and industrial control systems. One particular application domain has been shown suitable for the requirements of precision agriculture where such systems can improve yields, increase efficiency and reduce input usage. We present a data analysis and processing approach for distributed monitoring of crops and soil where hierarchical aggregation and modelling primitives contribute to the robustness of the network by alleviating communication bottlenecks and reducing the energy required for redundant data transmissions. The focus is on leveraging the fog computing paradigm to exploit local node computing resources and generate events towards upper decision systems. Key metrics are reported which highlight the improvements achieved. A case study is carried out on real field data for crop and soil monitoring with outlook on operational and implementation constraints., Comment: 6 pages, 9 figures

Published
2019

12. WSN and Fog Computing Integration for Intelligent Data Processing

Author

Mihai, Viorel, Hanganu, Cristina Elena, Stamatescu, Grigore, and Popescu, Dan

Subjects
Computer Science - Distributed, Parallel, and Cluster Computing
Abstract

Networked embedded systems endowed with sensing, computing, control and communication capabilities allow the development of various application scenarios and represent the building blocks of the Internet of Things (IoT) paradigm. Traditional data collection methods include multiple field level IoT systems that can relay data stemming from a network of distributed ground sensors directly to a cloud platform for storage, analysis and processing. In such applications however, rapid sensor deployment in unstructured environments represents a challenge to the overall robustness of the system. We discuss the fog and mist computing approaches to hierarchically process data along its path from source to destination. The several stages of intermediate data processing reduce the computational and communication effort in a gradual manner. A three-layer topology for smart data monitoring and processing is thus proposed and illustrated to improve the information to noise ratio in a reference scenario., Comment: 4 pages, 5 figures

Published
2019

13. The Seismic Behaviour of Composite Steel-Concrete Coupled Walls with Centred Openings

Author

Todea, Viorel, Dan, Daniel, Stoian, Valeriu, Floruț, Sorin-Codruț, Popescu, Dan-Adrian, di Prisco, Marco, Series Editor, Chen, Sheng-Hong, Series Editor, Vayas, Ioannis, Series Editor, Kumar Shukla, Sanjay, Series Editor, Sharma, Anuj, Series Editor, Kumar, Nagesh, Series Editor, Wang, Chien Ming, Series Editor, Mazzolani, Federico M., editor, Dubina, Dan, editor, and Stratan, Aurel, editor

Published
2022
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14. Comparative Study on the Behaviour of Composite Steel-Concrete Shear Walls Under Lateral Loads

Author

Todea, Viorel, Dan, Daniel, Stoian, Valeriu, Floruț, Sorin-Codruț, Popescu, Dan-Adrian, di Prisco, Marco, Series Editor, Chen, Sheng-Hong, Series Editor, Vayas, Ioannis, Series Editor, Kumar Shukla, Sanjay, Series Editor, Sharma, Anuj, Series Editor, Kumar, Nagesh, Series Editor, Wang, Chien Ming, Series Editor, Mazzolani, Federico M., editor, Dubina, Dan, editor, and Stratan, Aurel, editor

Published
2022
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15. Pharynx Reconstruction and Quality of Life

Author

Luiza Bejenaru, Paula, primary, Grigore, Raluca, additional, Popescu, Bogdan, additional, Nicolaescu, Alexandru, additional, Cojocărița-Condeescu, Mihnea, additional, Simion-Antonie, Catrinel, additional, Berteșteanu, Gloria, additional, Cirstea, Anca, additional, Diaconu, Teodora, additional, Taher, Bianca, additional, Rujan, Simona, additional, Popescu, Dan, additional, and V.G. Berteșteanu, Șerban, additional

Published
2022
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17. Building the Space Elevator: Lessons from Biological Design

Author

Popescu, Dan M. and Sun, Sean X.

Subjects
Physics - Space Physics, Physics - Applied Physics
Abstract

One of the biggest perceived challenges in building megastructures, such as the space elevator, is the unavailability of materials with sufficient tensile strength. The presumed necessity of very strong materials stems from a design paradigm which requires structures to operate at a small fraction of their maximum tensile strength (usually, 50% or less). This criterion limits the probability of failure by giving structures sufficient leeway in handling stochastic components, such as variability in material strength and/or external forces. While reasonable for typical engineering structures, low working stress ratios --- defined as operating stress as a fraction of ultimate tensile strength --- in the case of megastructures are both too stringent and unable to adequately control the failure probability. We draw inspiration from natural biological structures, such as bones, tendons and ligaments, which are made up of smaller substructures and exhibit self-repair, and suggest a design that requires structures to operate at significantly higher stress ratios, while maintaining reliability through a continuous repair mechanism. We outline a mathematical framework for analysing the reliability of structures with components exhibiting probabilistic rupture and repair that depend on their time-in-use (age). Further, we predict time-to-failure distributions for the overall structure. We then apply this framework to the space elevator and find that a high degree of reliability is achievable using currently existing materials, provided it operates at sufficiently high working stress ratios, sustained through an autonomous repair mechanism, implemented via, e.g., robots.

Published
2018

19. Semantic Segmentation of Small Region of Interest for Agricultural Research Applications

Author

Popescu, Dan, Ichim, Loretta, Sava, Octavian Andrei, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Nguyen, Ngoc Thanh, editor, Iliadis, Lazaros, editor, Maglogiannis, Ilias, editor, and Trawiński, Bogdan, editor

Published
2021
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23. Erg(r)odicity: Hidden Bias and the Growthrate Gain

Author

Rochman, Nash, Popescu, Dan, and Sun, Sean X.

Subjects
Quantitative Biology - Quantitative Methods
Abstract

Many single-cell observables are highly heterogeneous. A part of this heterogeneity stems from age-related phenomena: the fact that there is a nonuniform distribution of cells with different ages. This has led to a renewed interest in analytic methodologies including use of the "von Foerster equation" for predicting population growth and cell age distributions. Here we discuss how some of the most popular implementations of this machinery assume a strong condition on the ergodicity of the cell cycle duration ensemble. We show that one common definition for the term ergodicity, "a single individual observed over many generations recapitulates the behavior of the entire ensemble" is implied by the other, "the probability of observing any state is conserved across time and over all individuals" in an ensemble with a fixed number of individuals but that this is not true when the ensemble is growing. We further explore the impact of generational correlations between cell cycle durations on the population growth rate. Finally, we explore the "growth rate gain" - the phenomenon that variations in the cell cycle duration lead to an improved population-level growth rate - in this context. We highlight that, fundamentally, this effect is due to asymmetric division., Comment: 17 pages, 4 figures

Published
2017
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24. Fusioning Multiple Treatment Retina Images into a Single One

Author

Mocanu, Irina, Ichim, Loretta, Popescu, Dan, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Yang, Haiqin, editor, Pasupa, Kitsuchart, editor, Leung, Andrew Chi-Sing, editor, Kwok, James T., editor, Chan, Jonathan H., editor, and King, Irwin, editor

Published
2020
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26. Integrating UAV in IoT for RoI Classification in Remote Images

Author

Ichim, Loretta, Popescu, Dan, Hutchison, David, Editorial Board Member, Kanade, Takeo, Editorial Board Member, Kittler, Josef, Editorial Board Member, Kleinberg, Jon M., Editorial Board Member, Mattern, Friedemann, Editorial Board Member, Mitchell, John C., Editorial Board Member, Naor, Moni, Editorial Board Member, Pandu Rangan, C., Editorial Board Member, Terzopoulos, Demetri, Editorial Board Member, Tygar, Doug, Editorial Board Member, Weikum, Gerhard, Series Editor, 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, Woeginger, Gerhard, Editorial Board Member, Blanc-Talon, Jacques, editor, Helbert, David, editor, Philips, Wilfried, editor, Popescu, Dan, editor, and Scheunders, Paul, editor

Published
2018
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27. ORAL CANCER: ETIOLOGY AND THERAPEUTIC ASPECTS. LITERATURE REVIEW.

Author

Munteanu, Cristina Maria, Pătru, Ciprian Laurențiu, Popescu, Dan Alexandru, Boldeanu, Gabriela, Predescu, Anca Mihaela, Rădeanu, Alina Cristina, Andrei, Elena Cristina, and Liliac, Ilona Mihaela

Subjects
HEAD & neck cancer, PRECANCEROUS conditions, NATURAL history, PROGNOSIS, DIETARY patterns, ORAL mucosa
Abstract

This article provides a literature review on the causes and treatment of oral cancer. It discusses various risk factors, including age, gender, heredity, race, socio-economic status, and immunodeficiency. Local causes such as tobacco and alcohol use, chronic traumas, chronic infections, and the role of viruses are also explored. The review highlights the potential of probiotics, vitamins, omega-3 fatty acids, and compounds like curcumin in preventing oral cancer. The Mediterranean diet is also mentioned as a potential preventive measure. The article emphasizes the importance of early detection and management of precancerous lesions, as well as the role of dentists in patient care and prevention through education. Treatment options for oral cancer include surgery, radiation therapy, and adjuvant therapy, but these treatments can be expensive and harmful. The article provides a list of references for further research on related topics. [Extracted from the article]

Published
2024
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28. CLINICAL AND MORPHOLOGICAL ASPECTS OF GINGIVAL OVERGROWTH INDUCED BY FIXED ORTHODONTIC THERAPY.

Author

Rădeanu, Alina Cristina, Surpățeanu, Mihai, Popescu, Dan Alexandru, Pătru, Ciprian Laurențiu, Liliac, Ilona Mihaela, Andrei, Elena Cristina, Munteanu, Cristina Maria, and Cumpătă, Cristian Niky

Subjects
GINGIVAL hyperplasia, ORTHODONTIC retainers, FLUORESCENCE spectroscopy, DENTISTRY, ORTHODONTIC appliances, CARIOGENIC agents, ARCHES
Abstract

This article from the Romanian Journal of Oral Rehabilitation explores the clinical and morphological aspects of gingival overgrowth caused by fixed orthodontic therapy. The study involved analyzing biopsies of gingival mucosa from patients undergoing orthodontic treatment to understand the tissue changes. The main causes of gingival overgrowth during orthodontic treatment are increased plaque accumulation and excessive pressure from orthodontic forces. The article emphasizes the importance of oral hygiene and the correct duration and approach to orthodontic therapy in preventing gingival overgrowth. It also discusses the different types of gingival overgrowth and the need for a collaborative approach involving dentists, orthodontists, and maxillofacial surgeons for effective treatment. [Extracted from the article]

Published
2024
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29. Large Scale Wireless Sensor Networks Based on Fixed Nodes and Mobile Robots in Precision Agriculture

Author

Nicolae, Maximilian, Popescu, Dan, Merezeanu, Daniel, Ichim, Loretta, Ceccarelli, Marco, Series Editor, Hernandez, Alfonso, Editorial Board Member, Huang, Tian, Editorial Board Member, Velinsky, Steven A., Editorial Board Member, Takeda, Yukio, Editorial Board Member, Corves, Burkhard, Editorial Board Member, Aspragathos, Nikos A., editor, Koustoumpardis, Panagiotis N., editor, and Moulianitis, Vassilis C., editor

Published
2019
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31. Deep CNN Based System for Detection and Evaluation of RoIs in Flooded Areas

Author

Popescu, Dan, Ichim, Loretta, Cioroiu, George, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Gedeon, Tom, editor, Wong, Kok Wai, editor, and Lee, Minho, editor

Published
2019
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32. Detection of Cancerous Lesions with Neural Networks

Author

El-khatib, Hassan, Popescu, Dan, Ichim, Loretta, Hutchison, David, Editorial Board Member, Kanade, Takeo, Editorial Board Member, Kittler, Josef, Editorial Board Member, Kleinberg, Jon M., Editorial Board Member, Mattern, Friedemann, Editorial Board Member, Mitchell, John C., Editorial Board Member, Naor, Moni, Editorial Board Member, Pandu Rangan, C., Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Terzopoulos, Demetri, Editorial Board Member, Tygar, Doug, Editorial Board Member, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Rojas, Ignacio, editor, Joya, Gonzalo, editor, and Catala, Andreu, editor

Published
2019
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38. Monitoring and Evaluation of Flooded Areas Based on Fused Texture Descriptors

Author

Ichim, Loretta, Popescu, Dan, 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, Blanc-Talon, Jacques, editor, Penne, Rudi, editor, Philips, Wilfried, editor, Popescu, Dan, editor, and Scheunders, Paul, editor

Published
2017
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44. Complex Conditional Generative Adversarial Nets for Multiple Objectives Detection in Aerial Images

Author

Popescu, Dan, Ichim, Loretta, Docea, Andrei, 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, Cheng, Long, editor, Leung, Andrew Chi Sing, editor, and Ozawa, Seiichi, editor

Published
2018
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46. Hiding Malicious Content in PDF Documents

Author

Popescu, Dan-Sabin

Subjects
Computer Science - Cryptography and Security, I.7.2, K.6.5
Abstract

This paper is a proof-of-concept demonstration for a specific digital signatures vulnerability that shows the ineffectiveness of the WYSIWYS (What You See Is What You Sign) concept. The algorithm is fairly simple: the attacker generates a polymorphic file that has two different types of content (text, as a PDF document for example, and image: TIFF - two of the most widely used file formats). When the victim signs the dual content file, he/ she only sees a PDF document and is unaware of the hidden content inside the file. After obtaining the legally signed document from the victim, the attacker simply has to change the extension to the other file format. This will not invalidate the digital signature, as no bits were altered. The destructive potential of the attack is considerable, as the Portable Document Format (PDF) is widely used in e-government and in e-business contexts., Comment: 8 pages

Published
2012

47. Tendencies of International Career of Romanian Researchers: Brain Drain?

Author

Popescu, Dan, Patrasca, Mihaela, and Chivu, Iulia

Abstract

Recent economic and technological developments have led to a growing international demand for highly skilled human resources. The increased competition for human capital has determined numerous OECD countries to take special measures for attracting and retaining human capital in such fields as: information technology, biotechnology, nanotechnology, health care, etc. These measures have stimulated the emigration of highly skilled professionals, especially from less developed to more developed economies. In this international context, in the last decade, Romanian and other Eastern European people with an academic background have had a significant propensity towards emigration. This phenomenon is not surprising if one considers the limited (although increasing) number of attractive career opportunities in this region. Consequently, numerous scientists and other highly skilled individuals from Eastern Europe have been attracted by the United States, Canada and other Western countries, which have facilitated the access of certain categories of qualified foreigners. (Contains 5 tables, 3 figures, and 14 notes.)

Published
2006

49. Complex Image Processing Using Correlated Color Information

Author

Popescu, Dan, Ichim, Loretta, Gornea, Diana, Stoican, Florin, 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, Blanc-Talon, Jacques, editor, Distante, Cosimo, editor, Philips, Wilfried, editor, Popescu, Dan, editor, and Scheunders, Paul, editor

Published
2016
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