Cat Family Recognition by Using Convolution Neural Network

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@article{1705257,
      author = {Amit Kumar Pandey, Dr. Santosh Singh, Bipin Yadav},
      title = {Cat Family Recognition by Using Convolution Neural Network},
      journal = {Iconic Research And Engineering Journals},
      year = {2023},
      volume = {7},
      number = {6},
      pages = {64-69},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/17052571.pdf},
      abstract = {This project presents an automated solution for the recognition of various species within the cat family through the implementation of Convolutional Neural Networks (CNNs). Leveraging the TensorFlow and Keras libraries, the study addresses the challenge of accurately classifying images depicting Cheetahs, Leopards, Lions, Pumas, and Tigers. The methodology involves the preprocessing of image data, the construction of a specialized CNN architecture, and the utilization of categorical cross-entropy loss for multiclass classification. The model is trained and evaluated on a dataset comprising diverse cat species, demonstrating its efficacy in accurately identifying the species of a given cat image. The results indicate promising performance, showcasing the potential of CNNs in automating cat species recognition, with implications for wildlife monitoring and conservation initiatives.},
      keywords = {Cat Family, CNN, Image Classification, TensorFlow, Keras, Deep Learning, Convolutional Neural Networks, Image Data Generator.},
      month = {December},
  }