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ABSTRACT Different measures have been employed by livestock caretakers for the detection and monitoring of health and welfare status of their livestock. However, being performed manually has made the task a labor intensive, costly and time-consuming exercise. Various modern technologies have been explored by many studies to improve the livestock production, from among which computer vision has proven to be highly effective and efficient; nevertheless, a thorough investigation into the application of computer vision reveals noteworthy obstacles to embracing and implementing it in precision livestock farming such as cattle farming. Among the obstacles are 1) unavailability of reliable public cattle datasets and 2) lack of tested and trusted generalized methods/models employ in conducting research and experiment on new datasets. This paper presents an overview of the challenges and possible directions and future research opportunities of computer vision-based precision livestock farming.
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