- Chinese Core Journal
- Chinese Science Citation Database (CSCD) Source journal
- Journal of Citation Report of Chinese S&T Journals (Core Edition)
| Citation: |
ZHANG Zheng, ZOU Bosheng. Fish feeding behavior recognition model based on fusion of visual and water quality features[J]. Journal of South China Agricultural University, 2025, 46(4): 1-11.
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In industrial aquaculture, environmental factors such as lighting and water quality are complex. To improve the accuracy of fish feeding behavior recognition, in this study, we proposed a fish feeding behavior recognition model based on the fusion of visual and water quality features, namely MC-ConvNeXtV2.
To better capture the global features of different aggregation levels and the detailed features of feeding behavior, a context-aware local attention mechanism (Cloatt) was introduced in each convolution stage of ConvNeXtV2-T. To improve the behavior recognition performance of the model in high-density aquaculture, a multimodal feature fusion module (MFFM) was designed to achieve adaptive fusion of visual features and dissolve oxygen, temperature, and pH of water quality features. The experiment was conducted in a Micropterus salmoides culture factory, with a culture density of 160 fish/m3.
The experimental results showed that for the task of four feeding behaviors classification of fish school, the recognition accuracy, precision and recall of MC-ConvNeXtV2 model were 96.89%, 96.34%, and 96.59%, respectively. Compared with ConvNeXtV2-T, its indicators increased by 3.11, 2.42, and 2.72 percentage points, respectively.
The proposed fish feeding behavior recognition model offers a new approach for intelligent aquaculture management.
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