# Fish Detection in Fishways for Hydropower Stations Using Bidirectional Cross-Scale Feature Fusion
## 4 Application  
To verify the feasibility of the proposed method, fish species target detection in the complex fishway environment was conducted. The method ensures that fish ecological habitats are not disrupted while achieving accurate and rapid fish detection with minimal resource usage. We installed and deployed the detection equipment at the designated fishway next to the hydropower station on the Han River in Hubei, ensuring that the normal operation of the fishway was not affected. The detection equipment was installed at the inlet of the fishway, as shown in Figure 8. The underwater detection system consists of a fish passage box culvert and an encapsulated camera. The fish passage box culvert restricts the fish from passing through the fishway via the box. The proposed method in this study was deployed in the encapsulated camera to detect the fish passing through the channel. The underwater detection system was slowly lowered along a track on the inner wall of the fishway to the bottom and fixed in the corresponding position.  
Similarly, we installed the underwater detection device at the fishway outlet and used a Hikvision camera in the detection device to collect a dataset of fish species in the fishway. The camera resolution was 1920 \(\times\) 1080 pixels. To detect different fish migrations, the captured data were filtered based on different time segments and target fish species, creating a dataset for the fish migration in this season, as shown in Figure 9. This dataset includes four fish species: Schizothorax macropopon, Racoma waltoni, Rhynchocypris lagowskii, and Schizothorax ocnonori, with a total of 4233 images. Due to the presence of small fish with very short lengths, which could not be classified based on features and  
Figure 7: The performance of the proposed fishway fish detection model during the training and validation process on the Fish26 dataset, including various metrics.  
silhouettes, these small fish were uniformly labeled as \"Small Fish\". LabelImg software (version 1.8.6) was used for annotation, and the dataset was divided into training and validation sets in an 8:2 ratio using a random selection process.  
Through the computer system managed by the hydropower station authorities, our onsite detection equipment allows for real-time observation of fish passage and detection performance. Compared to traditional methods (manual detection), this approach significantly reduces manual intervention while improving both accuracy and efficiency. The detection results are shown in Figure 10. This method eliminates the need for intervention by fishway maintenance and management personnel. Additionally, analyzing the daily fish passage data can effectively provide guiding parameters for the rational operation of the fishway. At the same time, multiple datasets of different fish species can be collected. Detecting fish passage through the fishway ensures the scientific construction, reasonable operation, and management of fishway facilities. Additionally, it allows for real-time observation of fish passage in the system, effectively meeting the requirements for real-time fish detection and improving the efficiency of fishway monitoring.  
Figure 8: The 3D schematic of the underwater detection system, consisting of a fish passage box, culvert and an encapsulated camera, and its installation at the designated location at the fishway inlet after processing and assembly.  
Figure 9: The fishway detection system was installed at the designated position of the fishway outlet using an electric hoist, and underwater images of different fish species in the fishway were captured.