Lightweight improvement and global channel pruning tomato seedling grading model based on lightweight improvement and global channeling

Xiaoyan Zhao; Jiandong Fang; Yudong Zhao

doi:10.1117/12.3033139

5 July 2024 Lightweight improvement and global channel pruning tomato seedling grading model based on lightweight improvement and global channeling

Xiaoyan Zhao, Jiandong Fang, Yudong Zhao

Author Affiliations +

Proceedings Volume 13184, Third International Conference on Electronic Information Engineering and Data Processing (EIEDP 2024); 131842C (2024) https://doi.org/10.1117/12.3033139
Event: 3rd International Conference on Electronic Information Engineering and Data Processing (EIEDP 2024), 2024, Kuala Lumpur, Malaysia

Abstract

To achieve automatic grading of potting seedlings, improve performance, and reduce complexity, we collected and constructed a grading dataset using tomato potting seedlings as the test subject. We selected the YOLOv5n target detection model as the baseline model. We reduced the number of model parameters through lightweight improvements, integrated the similarity-based attention mechanism into the backbone network, enhanced the accuracy of potting seedling feature recognition by improving the CIOU loss function to EIOU, and performed global channel pruning on the improved model to further reduce its complexity. Experiments demonstrate the following results: the final model achieves a recall of 92.1%, an average precision mean of 94.9%, has 0.9×106M parameters, performs 2.1G floating-point operations, has a model weight size of 2.2M, and achieves a detection speed of 130 frames per second. Deployment and testing on edge devices confirm that the model achieves low computational requirements, has a small parameter count, maintains fast and accurate performance, and can be used for real-time classification of potting seedlings.

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

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Xiaoyan Zhao, Jiandong Fang, and Yudong Zhao "Lightweight improvement and global channel pruning tomato seedling grading model based on lightweight improvement and global channeling", Proc. SPIE 13184, Third International Conference on Electronic Information Engineering and Data Processing (EIEDP 2024), 131842C (5 July 2024); https://doi.org/10.1117/12.3033139

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KEYWORDS

Performance modeling

Data modeling

Target detection

Education and training

Neurons

Image enhancement

Convolution

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