An efficient layer interaction network for image recognition

Hanze Li

doi:10.1117/12.3042012

11 September 2024 An efficient layer interaction network for image recognition

Hanze Li

Proceedings Volume 13253, Fourth International Conference on Signal Image Processing and Communication (ICSIPC 2024); 132530D (2024) https://doi.org/10.1117/12.3042012
Event: 4th International Conference on Signal Image Processing and Communication, 2024, Xi'an, China

Abstract

In recent years, enhancing layer interaction has become an important aspect in CNNs, as it can improve the information flow and representation capability of models. With the introduction of attention mechanisms, methods for enhancing layer interaction have also become increasingly complex. In this paper, we reveal that existing layer interaction models exhibit high time complexity and inference time, thus reducing the training efficiency of the model. To address this issue, we propose an efficient layer interaction model named ELINet, which achieves enhanced layer interaction while maintaining low time complexity and inference time. We evaluated our proposed method on multiple datasets, including CIFAR-10, CIFAR-100, and the ImageNet-1K. By comparing the Top-1 accuracy and actual runtime, we demonstrated the effectiveness and efficiency of our proposed model.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Hanze Li "An efficient layer interaction network for image recognition", Proc. SPIE 13253, Fourth International Conference on Signal Image Processing and Communication (ICSIPC 2024), 132530D (11 September 2024); https://doi.org/10.1117/12.3042012

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