YOLOv5 marine fish target detection method based on attention mechanism and DropBlock
A target detection and attention technology, applied in the field of fish research, can solve problems such as affecting the speed and accuracy of target detection methods, unable to detect fish quickly, and unable to capture fish targets, so as to alleviate the phenomenon of overfitting and improve Clarity, the effect of reducing redundant features
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[0047] A YOLOv5 marine fish target detection method based on attention mechanism and DropBlock, including:
[0048] 1. Select and collect data sets;
[0049] 2. Data set labeling and division;
[0050] 3. Construct the YOLOv5 marine fish target detection model with attention mechanism and DropBlock;
[0051] 4. Use the constructed marine fish target detection model to detect fish.
[0052] Step 1 specifically includes:
[0053] Select appropriate fish sample images from public datasets, as well as artificially captured marine fish images from fish from China's waters.
[0054] Step 2 specifically includes:
[0055] 2.1 Use LabelImg labeling software to manually proofread and label the public data set obtained in step 1 to obtain the corresponding correct label data.
[0056] 2.2 Manually label the self-built fish dataset obtained in step 1 using LabelImg labeling software to obtain the corresponding label data.
[0057] 2.3 After the above steps, 10,325 fish images in the ...
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