CP-YOLOX-based Algorithm for Protein Target Detection in Cryo-electron Micrographs

doi:10.3969/j.issn.1006-2475.2023.11.018

Abstract

Abstract: Abstract： A cryo-electron micrograph target detection algorithm （Cryo-Protein YOLOX， CP-YOLOX） is proposed for the existing cryo-electron micrograph protein target detection algorithm with inadequate feature fusion and complex network model， missed detection and false detection. The algorithm mainly contains feature extraction module， feature fusion module， and output side. The feature extraction module applies the B-ResBlockX module proposed in this paper， which uses grouped filters to generate multiple feature channels to improve the feature fusion capability and capture more detailed features. The feature fusion module applies the FastHead module proposed in this paper， which uses multilevel dilated convolution module for feature fusion and simplifies the output to a single channel， which can have a more lightweight network structure without losing accuracy. In order to further improve the accuracy and convergence speed， the position loss function is added with the Euclidean distance constraint between the target frame and the prediction frame. Experimental results on public datasets EMPIAR-10028， EMPIAR-10081， and EMPIAR-10089 showed that the number of network parameters of the proposed algorithm was only 5.19×106， and the mAP（0.5） was improved by 2.4， 3.3 and 2.5 percentage points， respectively， compared with YOLOX.

Key words: Key words： cryo-electron micrographs, target detection, protein particle detection, lightweight

CLC Number:

TP389.41

OU Jia-cheng, ZENG An, JIN Liang. CP-YOLOX-based Algorithm for Protein Target Detection in Cryo-electron Micrographs[J]. Computer and Modernization, 2023, 0(11): 113-119.

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