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28 April 2023 Research on apple target detection algorithm based on improved YOLOv3
Mingbo Ma, Jian Wu, Bo Shao, YingBiao Hu
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Proceedings Volume 12626, International Conference on Signal Processing, Computer Networks, and Communications (SPCNC 2022); 126261D (2023) https://doi.org/10.1117/12.2674531
Event: International Conference on Signal Processing, Computer Networks, and Communications (SPCNC 2022), 2022, Zhuhai, China
Abstract
In order to solve the problems of low detection accuracy and poor robustness of fruits under natural conditions, an apple detection model based on improved yolov3 is proposed with apples in natural environment as the research object. Firstly, the ordinary convolution inside the residual network in DarkNet53 is replaced with a depth-separable convolution to improve the detection speed of the model while reducing the number of parameters in the network; secondly, the channel-space attention mechanism (Convolutional Block Attention Module, CBAM)module is added to the process of feature pyramid upsampling to further strengthen the model feature extraction and improve the recognition accuracy of overlapping apples; finally, the introduction of CIOU Loss complete cross-comparison loss function, which integrates the influence of the overlapping area, aspect ratio, centroid distance and other factors on the bounding box regression, makes the bounding box regression stable while the target detection accuracy is also improved. The experiments show that the improved model achieves a MAP (Mean Average Precision) value of 91.30% and an F1 value of 86% under the test set, which is 4.2 percentage points and 5 percentage points hight than the original model respectively.
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Mingbo Ma, Jian Wu, Bo Shao, and YingBiao Hu "Research on apple target detection algorithm based on improved YOLOv3", Proc. SPIE 12626, International Conference on Signal Processing, Computer Networks, and Communications (SPCNC 2022), 126261D (28 April 2023); https://doi.org/10.1117/12.2674531
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KEYWORDS
Convolution
Detection and tracking algorithms
Education and training
Data modeling
Target detection
Image processing
Information fusion
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