Research progress and frontier analysis of fine-grained image classification based on CiteSpace

Yifeng Lin

doi:10.1117/12.2643842

9 October 2022 Research progress and frontier analysis of fine-grained image classification based on CiteSpace

Yifeng Lin

Proceedings Volume 12246, 2nd International Conference on Signal Image Processing and Communication (ICSIPC 2022); 122461I (2022) https://doi.org/10.1117/12.2643842
Event: 2nd International Conference on Signal Image Processing and Communication (ICSIPC 2022), 2022, Qingdao, China

Abstract

With the growth of image classification models and the development of deep learning, the level of computer image classification has basically surpassed that of humans, but the level of fine-grained computer image classification is still weaker than that of humans, so fine-grained image classification is currently given a lot of attention. This paper carries out visualized analysis for the fine-grained image classification in terms of cooperation, scientific research, research trend and other aspects by CiteSpace software, and also points out that fine-grained image classification relies on CNN while looking into Transformer. However, fine-grained image classification has the problems of model reliance on prior knowledge (CNN), lack of sufficient data (Transformer), and lack of local relevance (CNN/Transformer), which can be solved by reducing the complexity of the model, transfer learning data augmentation, combination of CNN with Transformer, etc. On this basis, this paper indicates that Swin-Transformer has good generalization, hierarchy and translation invariance, and will become the main research direction for fine-grained image classification in the future.

Citation Download Citation

Yifeng Lin "Research progress and frontier analysis of fine-grained image classification based on CiteSpace", Proc. SPIE 12246, 2nd International Conference on Signal Image Processing and Communication (ICSIPC 2022), 122461I (9 October 2022); https://doi.org/10.1117/12.2643842

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