Dog Dataset

Research on dog datasets focuses on developing resources for analyzing canine images, particularly for applications in affective computing and pose estimation. Current efforts involve creating annotated datasets with facial landmarks for emotion recognition and leveraging pre-trained deep learning models, such as NASNet, to achieve high accuracy in image classification tasks. These datasets are crucial for advancing research in animal behavior understanding and improving the performance of computer vision algorithms in challenging real-world scenarios. The availability of robust, well-annotated datasets is essential for advancing the field and enabling broader applications in veterinary science and animal welfare.