Food Image Classification and Nutrition Detection Using CNN

@article{1703407,
      author = {Aarati Shankar Survase, Kimaya Sawant, Rinal Lokhande, Srushti Pawar, Prof. Prajwali Korde},
      title = {Food Image Classification and Nutrition Detection Using CNN},
      journal = {Iconic Research And Engineering Journals},
      year = {2022},
      volume = {5},
      number = {11},
      pages = {10-12},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/17034071.pdf},
      abstract = {Deep learning and the availability of greater datasets and computational resources have made classification more straightforward. In recent years, the convolutional neural network has become the most commonly used and popular image categorization approach. In this paper, various transfer learning approaches are used to classify images from an Indian cuisine dataset. Food plays a significant role in human life because it supplies us with a variety of nutrients, so it is crucial for everyone to keep track of their eating habits. As a result, food classification is a must for a better way of living. Pretrained models are employed in this project instead of typical ways of developing a model from the ground up, which saves computing time and money while also producing superior results. Dataset for Indian cuisine.},
      keywords = {Indian Food, Machine Learning, Food Image Classification},
      month = {May},
  }