Deep learning in computer vision: A critical review of emerging techniques and application scenarios

Deep learning has been overwhelmingly successful in computer vision (CV), natural language processing, and video/speech recognition. In this paper, our focus is on CV. We provide a critical review of recent achievements in terms of techniques and applications. We identify eight emerging techniques,...

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Bibliographic Details
Published inMachine learning with applications Vol. 6; p. 100134
Main Authors Chai, Junyi, Zeng, Hao, Li, Anming, Ngai, Eric W.T.
Format Journal Article
LanguageEnglish
Published Elsevier Ltd 01.12.2021
Elsevier
Subjects
Computer vision
Deep learning
Literature review
Machine learning
Deep learning
Literature review
Computer vision
Machine learning
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Summary:Deep learning has been overwhelmingly successful in computer vision (CV), natural language processing, and video/speech recognition. In this paper, our focus is on CV. We provide a critical review of recent achievements in terms of techniques and applications. We identify eight emerging techniques, investigate their origins and updates, and finally emphasize their applications in four key scenarios, including recognition, visual tracking, semantic segmentation, and image restoration. We recognize three development stages in the past decade and emphasize research trends for future works. The summarizations, knowledge accumulations, and creations could benefit researchers in the academia and participators in the CV industries.
ISSN:2666-8270
2666-8270
DOI:10.1016/j.mlwa.2021.100134