Advances in Sensing Techniques and Deep Learning for Food Quality Detection: Opportunities, Challenges, and Perspectives from Image Recognition to Multimodal Data Fusion
This review systematically compares CNNs, RNNs/LSTMs, Transformers, GNNs, GANs, and hybrid architectures, as well as transfer learning, self-supervised learning, contrastive learning, few-shot learning, lightweight networks, edge computing, and multimodal fusion.
Wei-Hao Wang, Zhi-Dan Jiang, Si-Si Yang et al.
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