IATEFF-YOLO: Focus on cow mounting detection during nighttime

Abstract

Mounting behaviour is an important characteristic of cows during oestrus. Real-time and accurate detection of cow mounting behaviour can shorten the calving-to-conception period and increase the economic benefits for dairy farms. Cow mounting behaviour occurs more often at night, and drastic scale changes in surveillance images caused by different distances between cows and camera, influence the detection of cow mounting. Existing methods are unable to address these challenges effectively. To address these challenges, this study collected 9392 images of Holstein cow mounting behaviour under intensive farming conditions using cameras and proposed an IATEFF-YOLO that is more suitable for cow mounting behaviour detection at nighttime and drastic scale changes in surveillance images caused by different distances between cows and camera. IATEFF-YOLO comprises an Illumination Adaptive Transformer (IAT) and an efficient feature fusion detector. The IAT enhances low-light images at night to enrich the cow mounting features, facilitating the subsequent detection of mounting behaviour. The efficient feature fusion detector, EFF-YOLO, enhances the feature fusion capability and further enable the detector to adapt to drastic scale changes in surveillance images caused by different distances between cows and camera. IATEFF-YOLO achieved a mean Average Precision of 99.3% and a detection speed of 102.0 f/s on test set. Compared with existing methods, IATEFF-YOLO achieved higher detection accuracy and faster detection speed during nighttime and drastic scale changes in surveillance images caused by different distances between cows and camera. IATEFF-YOLO can assist ranch breeders in achieving round-the-clock monitoring of cow oestrus, thereby enhancing oestrus detection efficiency.