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A Survey on Underwater Computer Vision

Salma González-Sabbagh, Antonio Robles‐Kelly • ACM Computing Surveys (2023)

Underwater computer vision has attracted increasing attention in the research community due to the recent advances in underwater platforms such as of rovers, gliders, autonomous underwater vehicles (AUVs) , and the like, that now make possi...

OPENALEX other-oa DOI: https://doi.org/10.1145/3578516

Computer Vision Syndrome: Prevalence and Associated Risk Factors among Undergraduates in a Tertiary Institution in North western Nigeria

Nwankwo B, Mumueh KP, Olorukooba AA, Usman NO • Kanem Journal of Medical Sciences (2021)

Background: Computers and other visual display devices have become essential in the present era and have led to a rise in computer-related health problems. Using computers in homes, universities and other institutions has increased output g...

DOAJ Open Access (DOAJ) DOI: 10.36020/kjms.2021.1501.003

Problems In Indoor Mapping and Modelling

S. Zlatanova, G. Sithole, M. Nakagawa, Q. Zhu • The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences (2013)

Research in support of indoor mapping and modelling (IMM) has been active for over thirty years. This research has come in the form of As-Built surveys, Data structuring, Visualisation techniques, Navigation models and so forth. Much of thi...

DOAJ Open Access (DOAJ) DOI: 10.5194/isprsarchives-XL-4-W4-63-2013

COVID-19 Control by Computer Vision Approaches: A Survey

Anwaar Ulhaq, Jannis Born, Asim Ali Khan, Douglas Pinto Sampaio Gomes et al. • IEEE Access (2020)

The COVID-19 pandemic has triggered an urgent call to contribute to the fight against an immense threat to the human population. Computer Vision, as a subfield of artificial intelligence, has enjoyed recent success in solving various comple...

OPENALEX cc-by DOI: https://doi.org/10.1109/access.2020.3027685 PMC: 8545281

Computer Perceptual Organization in Computer Vision

Sudeep Sarkar, Kim L. Boyer • Series in machine perception and artificial intelligence (1994)

This book describes the design of a complete, flexible system for perceptual organization in computer vision using graph theoretic techniques, voting methods, and an extension of the Bayesian networks called perceptual inference networks (P...

OPENALEX DOI: https://doi.org/10.1142/2421

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

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

Neural networks in geophysical applications

Mirko van der Baan, Christian Jutten B • Geophysics (2000)

Abstract Neural networks are increasingly popular in geophysics. Because they are universal approximators, these tools can approximate any continuous function with an arbitrary precision. Hence, they may yield important contributions to fin...

OPENALEX DOI: https://doi.org/10.1190/1.1444797

A Comprehensive Analysis of Multilayer Community Detection Algorithms for Application to EEG-Based Brain Networks

Maria Grazia Puxeddu, Maria Grazia Puxeddu, Manuela Petti, Manuela Petti et al. • Frontiers in Systems Neuroscience (2021)

Modular organization is an emergent property of brain networks, responsible for shaping communication processes and underpinning brain functioning. Moreover, brain networks are intrinsically multilayer since their attributes can vary across...

DOAJ Open Access (DOAJ) DOI: 10.3389/fnsys.2021.624183

Deep learning in nano-photonics: inverse design and beyond

Peter R. Wiecha, Arnaud Arbouet, Christian Girard, Otto L. Muskens • Photonics Research (2021)

Deep learning in the context of nano-photonics is mostly discussed in terms of its potential for inverse design of photonic devices or nano-structures. Many of the recent works on machine-learning inverse design are highly specific, and the...

OPENALEX Open Access DOI: https://doi.org/10.1364/prj.415960

Deep Learning in Remote Sensing: A Comprehensive Review and List of Resources

Xiao Xiang Zhu, Devis Tuia, Lichao Mou, Gui-Song Xia et al. • IEEE Geoscience and Remote Sensing Magazine (2017)

Central to the looming paradigm shift toward data-intensive science, machine-learning techniques are becoming increasingly important. In particular, deep learning has proven to be both a major breakthrough and an extremely powerful tool in ...

OPENALEX Open Access DOI: https://doi.org/10.1109/mgrs.2017.2762307