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@article{194113,
        author = {Naveenraj MC and Pavithra R and Harivengatesh S and Kabilan M and Shaheela Y},
        title = {RECIPE GENERATION BASED ON FOOD IMAGE RECOGNITION USING DEEP LEARNING},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {10},
        pages = {2232-2238},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=194113},
        abstract = {Recipe generation based on food image recognition has become a new way to help users with meal planning and cooking. This project suggests using a deep learning approach that employs Convolutional Neural Networks (CNNs) to analyze food images and automatically create recipes. The system is trained on a large dataset of food images to learn visual features, ingredient patterns, and dish characteristics. When it receives an input image, the trained model classifies the dish and identifies the ingredients, then synthesizes a recipe. The output includes a detailed list of ingredients and step-by-step cooking instructions. This smart system improves the user experience by offering personalized cooking suggestions and reducing the effort needed for manual recipe searches.},
        keywords = {Deep Learning, Convolutional Neural Networks (CNN), Food Image Recognition, Recipe Generation, Ingredient Identification.},
        month = {March},
        }