TY  - EJOU
AU  - Ganesh, Narayanan 
AU  - Shankar, Rajendran 
AU  - Mahdal, Miroslav 
AU  - Murugan, Janakiraman Senthil 
AU  - Chohan, Jasgurpreet Singh 
AU  - Kalita, Kanak 

TI  - Exploring Deep Learning Methods for Computer Vision Applications across Multiple Sectors: Challenges and Future Trends
T2  - Computer Modeling in Engineering \& Sciences

PY  - 2024
VL  - 139
IS  - 1
SN  - 1526-1506

AB  - Computer vision (CV) was developed for computers and other systems to act or make recommendations based on visual inputs, such as digital photos, movies, and other media. Deep learning (DL) methods are more successful than other traditional machine learning (ML) methods in CV. DL techniques can produce state-of-the-art results for difficult CV problems like picture categorization, object detection, and face recognition. In this review, a structured discussion on the history, methods, and applications of DL methods to CV problems is presented. The sector-wise presentation of applications in this paper may be particularly useful for researchers in niche fields who have limited or introductory knowledge of DL methods and CV. This review will provide readers with context and examples of how these techniques can be applied to specific areas. A curated list of popular datasets and a brief description of them are also included for the benefit of readers.
KW  - Neural network; machine vision; classification; object detection; deep learning

DO  - 10.32604/cmes.2023.028018