Artificial Intelligence Methods for Pet Emotions Recognition

Analyzing emotions in cats is a subject that comes with difficulties in interpretation. The subtle facial expressions of these animals make deciphering their emotional signals a challenge. The work focuses on the task of classifying feline emotions from images. It aims to test whether deep learning networks can recognize the primary emotional states of these animals on real (non-laboratory) image data. The results obtained in this work provide a basis for further research in this area. Future studies can focus on refining the parameters of existing models, developing advanced data analysis techniques, and exploring new classification models. Further research has the potential to contribute to a better understanding of emotional states in cats and improve the effectiveness of classification processes based on authentic images.