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Generative Adversarial Networks in Computer Vision

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...

OPENALEX Open Access DOI: https://doi.org/10.1145/3439723

Emerging Trends in Autonomous Vehicle Perception: Multimodal Fusion for 3D Object Detection

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

Crowd Analysis Using Computer Vision Techniques

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...

OPENALEX Open Access DOI: https://doi.org/10.1109/msp.2010.937394

Attention mechanisms in computer vision: A survey

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 ...

OPENALEX cc-by DOI: https://doi.org/10.1007/s41095-022-0271-y

Computer Vision and Image Processing: A Paper Review

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...

OPENALEX cc-by-sa DOI: https://doi.org/10.29099/ijair.v2i1.42

Euclid Quick Data Release (Q1)

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

Fashion Meets Computer Vision

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...

OPENALEX Open Access DOI: https://doi.org/10.1145/3447239

Computer Vision Metrics

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...

OPENALEX Open Access DOI: https://doi.org/10.1007/978-1-4302-5930-5

Identifying people’s energy information needs through Energy Citizen Personas

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

Computer Vision for Autonomous Vehicles

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...

OPENALEX Open Access DOI: https://doi.org/10.1561/0600000079

Survey on categorical data for neural networks

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...

OPENALEX cc-by DOI: https://doi.org/10.1186/s40537-020-00305-w

Digital Local Return Services and Purchase Intention in Cross-Border E-Commerce: A Risk–Trust Perspective

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

Neural Network Learning

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...

OPENALEX DOI: https://doi.org/10.1017/cbo9780511624216

Neural networks and their applications

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...

OPENALEX DOI: https://doi.org/10.1063/1.1144830

On neural networks.

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...

OPENALEX Open Access