An attention-enhanced neural network with distillation training for barcode detection

Zijian Wang; Zhiyuan Su

doi:10.1117/12.2678979

25 May 2023 An attention-enhanced neural network with distillation training for barcode detection

Zijian Wang, Zhiyuan Su

Proceedings Volume 12712, International Conference on Cloud Computing, Performance Computing, and Deep Learning (CCPCDL 2023); 1271210 (2023) https://doi.org/10.1117/12.2678979
Event: International Conference on Cloud Computing, Performance Computing, and Deep Learning (CCPCDL 2023), 2023, Huzhou, China

Abstract

Barcodes have played an essential role in our daily life. Localizing, or detecting them in real scenes in a fast and robust way has many practical applications. Recently, some deep learning-based methods have shown great potential in object detection. However, because barcodes are placed at any angle, vertical bounding boxes cannot sufficiently capture accurate orientation and scale information. In this paper, we propose a barcode detector that performs dense prediction to accurately locate the position of pixels belonging to the barcode region. For better detection performance, we design a spatial attention module to integrate global information adaptively, which can be easily plugged into the prediction backbone. Meanwhile, we employ the knowledge distillation training strategy to train a small student network with the help of a heavy teacher network. Extensive experiment results demonstrate that our method can perform real-time speed on CPU environments and locate barcodes in images with complex scenes.

Citation Download Citation

Zijian Wang and Zhiyuan Su "An attention-enhanced neural network with distillation training for barcode detection", Proc. SPIE 12712, International Conference on Cloud Computing, Performance Computing, and Deep Learning (CCPCDL 2023), 1271210 (25 May 2023); https://doi.org/10.1117/12.2678979

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