Facial Emotion Recognition of Cat Breeds by Using Convolution Neural Network

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@article{1705255,
      author = {Amit Kumar Pandey, Poonam Jain, Bipin Yadav, Vikas Pandey},
      title = {Facial Emotion Recognition of Cat Breeds by Using Convolution Neural Network},
      journal = {Iconic Research And Engineering Journals},
      year = {2023},
      volume = {7},
      number = {6},
      pages = {58-63},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1705255.pdf},
      abstract = {Facial expressions play a pivotal role in decoding the emotional states of animals, and this research delves into the domain of cat facial emotion recognition utilizing Convolutional Neural Network (CNN) algorithms. Drawing inspiration from analogous studies on dog facial expressions, our investigation focuses on the intricate task of detecting and classifying emotional expressions in cats. Leveraging a diverse dataset encompassing various cat breeds and emotional states, the CNN model demonstrates its efficacy with minimal preprocessing. The training process involves careful dataset augmentation and optimizer fine-tuning, ensuring the model's ability to generalize effectively. The results exhibit the model's proficiency in distinguishing between different emotional states in cats, presenting a promising avenue for further exploration in feline behavior analysis. This research contributes to the growing field of animal emotion recognition, shedding light on the subtleties of cat facial expressions through the lens of advanced machine learning techniques.},
      keywords = {Cat Facial Expressions, Convolution Neural Network, Kerasmodule, Emotion Detection.},
      month = {December},
  }