Classification in dynamic videos via a slow-fast network

Miao Zang; Hongfei Zhao; Yingying Kang; Ruixin Zhu

doi:10.1117/12.2687631

28 August 2023 Classification in dynamic videos via a slow-fast network

Miao Zang, Hongfei Zhao, Yingying Kang, Ruixin Zhu

Proceedings Volume 12724, Second International Conference on Biomedical and Intelligent Systems (IC-BIS 2023); 127242B (2023) https://doi.org/10.1117/12.2687631
Event: Second International Conference on Biomedical and Intelligent Systems (IC-BIS2023), 2023, Xiamen, China

Abstract

For a long time, classification in dynamic videos on public datasets have been a hot research topic. However, in medical image processing, many methods still use traditional machine learning methods to address the problem of cellular dynamics classification. In this study, we paid more attention in the morphological changes of lymphocytes in healthy mice after skin transplantation. We applied a typical deep learning network Slow-Fast into cellular dynamics classification task, in which we incorporated data augmentation techniques such as rotation and reverse ordering to alleviate the overfitting problem to a great extent. Our method achieved better performance on the live-cell video dataset compared to previous approaches.

Citation Download Citation

Miao Zang, Hongfei Zhao, Yingying Kang, and Ruixin Zhu "Classification in dynamic videos via a slow-fast network", Proc. SPIE 12724, Second International Conference on Biomedical and Intelligent Systems (IC-BIS 2023), 127242B (28 August 2023); https://doi.org/10.1117/12.2687631

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