Illness and Gender Classification of Cattle

Cattles are one of the most important components of the global agriculture industry as they provide essential resources like meat and dairy products. This is the reason cattle health is very crucial to ensure animal welfare. This paper presents a deep learning model designed to classify cattles based on gender and diagnose illness in an efficient manner. In this paper two different datasets have been used, one for gender classification and the other for illness detection. Through an extensive dataset of cattle images, the model designed using deep learning techniques learns to distinguish between male and female cattle with a high degree of accuracy. Additionally, the model designed here has the capability of detecting signs of illness or distress in cattles based on visual cures, such as changes in posture, skin condition and facial expressions. The model can be proved helpful in timely intervention, therefore improving overall animal welfare economic. Moreover, this research opens doors for the development of similar models in the broader context of livestock management and animal health.