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Academic Articles & Research Papers
Showing 20 of 1,033 academic articles
Zhengwei Wang, Qi She, Tomas Emmanuel Ward • ACM Computing Surveys
(2021)
Generative adversarial networks (GANs) have been extensively studied in the past few years. Arguably their most significant impact has been in the area of computer vision where great advances have been made in challenges such as plausible i...
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Open Access
DOI: https://doi.org/10.1145/3439723
Thomas Baltzer Moeslund, Erik Granum • Computer Vision and Image Understanding
(2001)
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DOI: https://doi.org/10.1006/cviu.2000.0897
Simegnew Yihunie Alaba, Ali C. Gurbuz, John E. Ball • World Electric Vehicle Journal
(2024)
The pursuit of autonomous driving relies on developing perception systems capable of making accurate, robust, and rapid decisions to interpret the driving environment effectively. Object detection is crucial for understanding the environmen...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/wevj15010020
Julio C. S. Jacques, Soraia Raupp Musse, Cláudio R. Jung • IEEE Signal Processing Magazine
(2010)
This article presents a survey on crowd analysis using computer vision techniques, covering different aspects such as people tracking, crowd density estimation, event detection, validation, and simulation. It also reports how related the ar...
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Open Access
DOI: https://doi.org/10.1109/msp.2010.937394
Meng-Hao Guo, Tian-Xing Xu, Jiangjiang Liu, Zheng-Ning Liu et al. • Computational Visual Media
(2022)
Humans can naturally and effectively find salient regions in complex scenes. Motivated by this observation, attention mechanisms were introduced into computer vision with the aim of imitating this aspect of the human visual system. Such an ...
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DOI: https://doi.org/10.1007/s41095-022-0271-y
Victor Wiley, Thomas Lucas • International Journal of Artificial Intelligence Research
(2018)
Computer vision has been studied from many persective. It expands from raw data recording into techniques and ideas combining digital image processing, pattern recognition, machine learning and computer graphics. The wide usage has attracte...
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DOI: https://doi.org/10.29099/ijair.v2i1.42
Bazzanini L., Angora G., Bergamini P., Meneghetti M. et al. • Astronomy & Astrophysics
(2026)
Strong gravitational lensing (SL) by galaxy clusters is a powerful probe of their inner mass distribution and a key test bed for cosmological models. However, the detection of SL events in wide-field surveys such as Euclid requires robust a...
DOAJ
Open Access (DOAJ)
DOI: 10.1051/0004-6361/202557590
Wen-Huang Cheng, Sijie Song, Chieh-Yun Chen, Shintami Chusnul Hidayati et al. • ACM Computing Surveys
(2021)
Fashion is the way we present ourselves to the world and has become one of the world’s largest industries. Fashion, mainly conveyed by vision, has thus attracted much attention from computer vision researchers in recent years. Given the rap...
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Open Access
DOI: https://doi.org/10.1145/3447239
Clayton Blehm, Seema Vishnu, Ashbala Khattak, Shrabanee Mitra et al. • Survey of Ophthalmology
(2005)
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DOI: https://doi.org/10.1016/j.survophthal.2005.02.008
Scott Krig • Apress eBooks
(2014)
Computer Vision Metrics provides an extensive survey and analysis of over 100 current and historical feature description and machine vision methods, with a detailed taxonomy for local, regional and global features. This book provides necess...
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Open Access
DOI: https://doi.org/10.1007/978-1-4302-5930-5
Ajesh Kumar, Toni Kuronen, Bilal Naqvi, Salla Annala et al. • Energy Informatics
(2026)
Abstract Energy Citizenship refers to individuals and communities participating, sometimes begrudgingly, in adopting energy solutions, whether sustainable or not. When enacted positively, it advances the green energy transition. There are s...
DOAJ
Open Access (DOAJ)
DOI: 10.1186/s42162-026-00691-0
Joel Janai, Fatma Güney, Aseem Behl, Andreas Geiger • Foundations and Trends® in Computer Graphics and Vision
(2020)
Recent years have witnessed enormous progress in AI-related fields such as computer vision, machine learning, and autonomous vehicles. As with any rapidly growing field, it becomes increasingly difficult to stay up-to-date or enter the fiel...
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Open Access
DOI: https://doi.org/10.1561/0600000079
David Alexander Forsyth, Jean Ponce (2002)
From the Publisher:
The accessible presentation of this book gives both a general view of the entire computer vision enterprise and also offers sufficient detail to be able to build useful applications. Users learn techniques that have pro...
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Qi‐Jun Zhang, K.C. Gupta • Artech House, Inc. eBooks
(2000)
From the Publisher:
Discover the new, unconventional alternatives for conquering RF and microwave design and modeling problems using neural networks information processing systems that can learn, generalize, and even allow model developm...
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John Hancock, Taghi M. Khoshgoftaar • Journal Of Big Data
(2020)
Abstract This survey investigates current techniques for representing qualitative data for use as input to neural networks. Techniques for using qualitative data in neural networks are well known. However, researchers continue to discover n...
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DOI: https://doi.org/10.1186/s40537-020-00305-w
Xianfa Shi, Miao Su, Keun-sik Park • Journal of Theoretical and Applied Electronic Commerce Research
(2026)
Cross-border e-commerce offers consumers broader product access, yet uncertainty surrounding returns continues to suppress online purchase decisions. This study conceptualizes digital local return services as a digital assurance mechanism i...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/jtaer21060165
K.J. Hunt, Daniel G. Sbarbaro, R. Żbikowski, P.J. Gawthrop • Automatica
(1992)
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DOI: https://doi.org/10.1016/0005-1098(92)90053-i
Martin Anthony, Peter L. Bartlett • Cambridge University Press eBooks
(1999)
First published in 1999, this book describes theoretical advances in the study of artificial neural networks. It explores probabilistic models of supervised learning problems, and addresses the key statistical and computational questions. R...
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DOI: https://doi.org/10.1017/cbo9780511624216
Chris M. Bishop • Review of Scientific Instruments
(1994)
Neural networks provide a range of powerful new techniques for solving problems in pattern recognition, data analysis, and control. They have several notable features including high processing speeds and the ability to learn the solution to...
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DOI: https://doi.org/10.1063/1.1144830
Jiří Beneš • Czech digital mathematics library
(1990)
JIŘÍ BENEŠTypical neural network models representing a broad survey of actual trends are considered in an unifying way as Complexes subject to specific control systems, called Formators which may have a two-level arrangement and incorporate...
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