Identifying Ingredients From Food Images And Generating Recipe

Registration ID: IJNRD_195601

Published ID: IJNRD2305683

DOI: Click Here to Get

Ninad Shirsat , Ronit Patil , Kunal Bumb , Atharv Satpute

Machine Learning, Semantic Integration, Data Augmentation, Probabilistic Modelling, Algorithm encoding.

Identifying ingredients from food images and generating recipe problem involves the task of creating a recipe with a desired dish image as input. In recent years, there has been increasing interest in developing machine learning methods to solve this problem. This article presents a review of the current state of the art of generating recipes, focusing on the various techniques that have been proposed to solve this problem, including neural networks, probabilistic modelling and so on. and rules-based systems. The paper also discusses challenges that still need to be addressed in the field, such as the lack of large-scale datasets and the difficulty of modelling complex cooking techniques. Finally, the paper highlights several potential future directions for generating recipe research, such as incorporating additional sources of information, such as users' nutritional preferences and needs, into the model formula form.

Published Paper   E-Certificate

Ninad Shirsat, Ronit Patil, Kunal Bumb, & Atharv Satpute (May-2023). Identifying Ingredients From Food Images And Generating Recipe. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 8(5), g687-g693. https://ijnrd.org/papers/IJNRD2305683.pdf

Volume 8 Issue 5, May-2023

Pages : g687-g693

Paper Reg. ID: IJNRD_195601

Published Paper Id: IJNRD2305683

Downloads: 000121986

Research Area: Engineering

Country: Pune, Maharashtra, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2305683.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2305683

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

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