Method of fruit and vegetable classification based on fusion pruning

Songtao Jin; Qiliang Zhang; Yu Qian

doi:10.1117/12.3034070

13 June 2024 Method of fruit and vegetable classification based on fusion pruning

Songtao Jin, Qiliang Zhang, Yu Qian

Proceedings Volume 13180, International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2024); 131802B (2024) https://doi.org/10.1117/12.3034070
Event: International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2024), 2024, Guangzhou, China

Abstract

Summary Object detection is an important direction of computer vision, and small Object detection has long been a difficult point in computer vision. With the progress of satellite and remote sensing technology, there are a large number of highdefinition remote sensing images every day. Because the target's feature map will shift after the target passes through the deep convolution network, which has a great impact on small target detection. In order to solve this problem, we introduce the receptive field module RFB in the relevant algorithm to enhance the discrimination of small target features. We further introduced the ASPP spatial pyramid module into the backbone network to expand the receptive field of the backbone network, so as to strengthen the detection of small and medium-sized targets. In order to evaluate its effectiveness, we carried out experiments in YOLOX target detection algorithm. The results show that this improvement can significantly improve the detection accuracy of small targets without affecting the reasoning speed.

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

Citation Download Citation

Songtao Jin, Qiliang Zhang, and Yu Qian "Method of fruit and vegetable classification based on fusion pruning", Proc. SPIE 13180, International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2024), 131802B (13 June 2024); https://doi.org/10.1117/12.3034070

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Data modeling

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Image classification

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Visual process modeling

Object detection

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