Data enhancement method based on attention activation map

Jian Guo; Quansheng Dou

doi:10.1117/12.2681048

23 May 2023 Data enhancement method based on attention activation map

Jian Guo, Quansheng Dou

Proceedings Volume 12645, International Conference on Computer, Artificial Intelligence, and Control Engineering (CAICE 2023); 126451R (2023) https://doi.org/10.1117/12.2681048
Event: International Conference on Computer, Artificial Intelligence, and Control Engineering (CAICE 2023), 2023, Hangzhou, China

Abstract

Overfitting is a major problem faced by deep learning, and data enhancement is an effective means to mitigate it. Erasure-based data enhancement improves model generalization by generating new training samples, but these methods lead to over-erasure and under-erasure problems due to the random nature of erasure. To alleviate these problems, this paper proposes a new attention activation map-based image erasure method: Aag-dem, selectively erase the relevant regions of the image to generate high-quality training data and finally a large number of experiments are done to prove the effectiveness and generality of the method, and the performance of the baseline is improved to some extent.

Citation Download Citation

Jian Guo and Quansheng Dou "Data enhancement method based on attention activation map", Proc. SPIE 12645, International Conference on Computer, Artificial Intelligence, and Control Engineering (CAICE 2023), 126451R (23 May 2023); https://doi.org/10.1117/12.2681048

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