Accurate classification and identification of chicken parts are critical to improve the productivity and processing speed in poultry processing plants. However, the overlapping of chicken parts has an impact on the effectiveness of the identification process. To solve this issue, this study proposed a real-time classification and detection method for chicken parts, utilizing YOLOV4 deep learning. The method can identify segmented chicken parts on the assembly line in real time and accurately, thus improving the efficiency of poultry processing. First, 600 images containing multiple chicken par...
