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Abstract：
Chicken behavior recognition is crucial for a number of reasons, including promoting animal welfare, ensuring the early detection of health issues, optimizing farm management practices, and contributing to more sustainable and ethical poultry farming. In this paper, we introduce a technique for recognizing chicken behavior on edge computing devices based on video sensing mosaicing. Our method combines video sensing mosaicing with deep learning to accurately identify specific chicken behaviors from videos. It attains remarkable accuracy, achieving 79.61% with MobileNetV2 for chickens demonstrating three types of behavior. These findings underscore the efficacy and promise of our approach in chicken behavior recognition on edge computing devices, making it adaptable for diverse applications. The ongoing exploration and identification of various behavioral patterns will contribute to a more comprehensive understanding of chicken behavior, enhancing the scope and accuracy of behavior analysis within diverse contexts.
摘要：
鸡的行为识别是至关重要的，原因有很多，包括促进动物福利，确保健康问题的早期发现，优化农场管理实践，并为更可持续和道德的家禽养殖做出贡献。在本文中,我们介绍了一种基于视频感知镶嵌的边缘计算设备上的鸡的行为识别技术。我们的方法将视频感知镶嵌与深度学习相结合，可以从视频中准确识别特定的鸡行为。它达到了惊人的准确性，用MobileNetV2对表现出三种行为的鸡达到79.61%。这些发现强调了我们的方法在边缘计算设备上进行鸡行为识别的有效性和前景。使其适应不同的应用。不断探索和识别各种行为模式将有助于更全面地了解鸡的行为，提高不同背景下行为分析的范围和准确性。
