Identification of Buffalo Breeds Using Self-Activated-Based Improved Convolutional Neural Networks

The livestock of Pakistan includes different animal breeds utilized for milk farming and exporting worldwide. Buffalo have a high production rate, is the third-largest milk-producing country, its increasing over time. Hence, it essential to recognize best breed milk- meat yield meet world’s demands production. has second-largest number buffalos among countries worldwide, where Neli-Ravi most common. extensive demand Neli Ravi resulted in new cross-breed “Neli-Ravi” 1960s. Identifying segregating from other buffalo crucial concern Pakistan’s dairy-production centers. Therefore, automatic detection classification are required. In this research, computer-vision-based recognition framework proposed identify classify breeds. employs self-activated-based improved convolutional neural networks (CNN) combined with self-transfer learning. Moreover, feature maps extracted CNN further transferred obtain rich vectors. Different machine learning (Ml) classifiers adopted evaluated on two breeds, namely, Khundi, one additional target class contains collectively called Mix. research achieves maximum 93% accuracy using SVM more than 85% employing recent variants.