A context-aware dropout-based occlusion-adaptive network for robust facial landmark and emotion detection

Abstract We present CAD-Net, a Context-Aware Dropout-based Occlusion-Adaptive Network for robust facial landmark detection (FLD) and facial expression recognition (FER) under challenging real-world conditions. Clinical and in-the-wild settings frequently involve strong occlusions (e.g., masks, medic...

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主要な著者:	Muhammad Sadiq, Yunsheng Zhang, Yu Zhou, Mohammad Sultan Mahmud, Muhammad Azhar, Muhammad Hanif Durad, Junwei Liang
フォーマット:	Artigo
言語:	Inglês
出版事項:	Springer 2026-04-01
シリーズ:	Journal of King Saud University: Computer and Information Sciences
主題:	Facial landmark detection Facial expression recognition Occlusion handling Context-aware dropout Low-rank learning Telemedicine
オンライン･アクセス:	https://doi.org/10.1007/s44443-026-00705-7
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