Technology of Graphic & Image
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App. Res. of Comp. Printed Article
Vol. 40, 2023 No. 9
2863-2868

Fine-grained visual classification method based on knowledge distillation and target regions selection

Zhao Tingting
Gao Huan
Chang Yuguang
Chen Yarui
Wang Yuan
Yang Jucheng
College of Artificial Intelligence, Tianjin University of Science & Technology, Tianjin 300457, China
DOI: 10.19734/j.issn.1001-3695.2022.12.0809

Abstract

Fine-grained visual classification(FGVC) is extremely challenging due to the subtle inter-class differences and the large intra-class differences. In order to learn the embedded features of fine-grained images efficiently, this paper attempted to introduce the idea of knowledge distillation to FGVC, and proposed TRS-DeiT, which was equipped with the common advantages of CNN models and Transformer models simultaneously. Besides, it proposed a novel target regions selection module in TRS-DeiT to obtain the most discriminative regions. It employed a contrastive loss function that measured the similarity of images to distinguish the confusable classes in the task. Finally, it demonstrated the effectiveness of the proposed TRS-DeiT model on CUB-200-2011, Stanford Cars and Stanford Dogs datasets, which achieved the accuracy of 90.8%, 95.0% and 95.1% respectively. The experimental results show that the proposed model outperforms the traditional models. Furthermore, the visualization results further illustrate that the attention learned by the proposed model mainly focuses on recognizing objects, thus contributes to fine-grained visual classification tasks.

Foundation Support

国家自然科学基金资助项目(61976156)
天津市企业科技特派员项目(20YDTPJC00560)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2022.12.0809
Publish at: Application Research of Computers Printed Article, Vol. 40, 2023 No. 9
Section: Technology of Graphic & Image
Pages: 2863-2868
Serial Number: 1001-3695(2023)09-048-2863-06

Publish History

[2023-03-03] Accepted Paper
[2023-09-05] Printed Article

Cite This Article

赵婷婷, 高欢, 常玉广, 等. 基于知识蒸馏与目标区域选取的细粒度图像分类方法 [J]. 计算机应用研究, 2023, 40 (9): 2863-2868. (Zhao Tingting, Gao Huan, Chang Yuguang, et al. Fine-grained visual classification method based on knowledge distillation and target regions selection [J]. Application Research of Computers, 2023, 40 (9): 2863-2868. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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