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Deep Learning for Computer Vision: A Brief Review

Athanasios S. Voulodimos, Nikolaos D. Doulamis, Anastasios D. Doulamis, Eftychios E. Protopapadakis • Computational Intelligence and Neuroscience (2018)

Over the last years deep learning methods have been shown to outperform previous state-of-the-art machine learning techniques in several fields, with computer vision being one of the most prominent cases. This review paper provides a brief ...

OPENALEX cc-by DOI: https://doi.org/10.1155/2018/7068349 PMC: 5816885

Application of Deep Learning in Food: A Review

Lei Zhou, Chu Zhang, Fei Liu, Zhengjun Qiu et al. • Comprehensive Reviews in Food Science and Food Safety (2019)

Deep learning has been proved to be an advanced technology for big data analysis with a large number of successful cases in image processing, speech recognition, object detection, and so on. Recently, it has also been introduced in food sci...

OPENALEX DOI: https://doi.org/10.1111/1541-4337.12492

Object Detection With Deep Learning: A Review

Zhong‐Qiu Zhao, Peng Zheng, Shou-Tao Xu, Xindong Wu • IEEE Transactions on Neural Networks and Learning Systems (2019)

Due to object detection's close relationship with video analysis and image understanding, it has attracted much research attention in recent years. Traditional object detection methods are built on handcrafted features and shallow trainable...

OPENALEX Open Access DOI: https://doi.org/10.1109/tnnls.2018.2876865

Diversity in Machine Learning

Zhiqiang Gong, Ping Zhong, Weidong Hu • IEEE Access (2019)

Machine learning methods have achieved good performance and been widely applied in various real-world applications. They can learn the model adaptively and be better fit for special requirements of different tasks. Generally, a good machine...

OPENALEX Open Access DOI: https://doi.org/10.1109/access.2019.2917620

Prototype-oriented contrastive mean-teacher for unsupervised domain adaptive object detection

Qi Cao, Jianwen Tao, Yufang Dan, Di Zhou • Scientific Reports (2026)

Abstract Unsupervised domain adaptive object detection (UDA-OD) aims to deploy a detector trained on source domain(s) to a new, unlabeled target domain. Carrying out mean-teacher self-training for UDA-OD poses a significant challenge, given...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41598-026-44991-7

Computer vision and AI-based cell phone usage detection in restricted zones of manufacturing industries

Uttam U. Deshpande, Supriya Shanbhag, Ramesh Koti, Ameet Chate et al. • Frontiers in Computer Science (2025)

Phone calls are strictly forbidden in certain locations due to the potential security threats. Mobile phones’ growing capabilities have also increased the risk of their misuse in places that are restricted, like manufacturing plants. Unauth...

DOAJ Open Access (DOAJ) DOI: 10.3389/fcomp.2025.1535775

InsDD-YOLO: Detection of Transmission Line Insulator Damage Based on the Improved YOLOv13 Model

Phat T. Nguyen, Duy C. Huynh, Loc D. Ho, Ha T. Tran et al. • IEEE Access (2025)

Amidst the rapid global expansion of smart grids, ensuring the safety and reliability of power transmission systems has become paramount. Insulators are critical components of high-voltage transmission lines, providing both electrical insul...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2025.3648259