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INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016 Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI) |
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| Paper Title: | Machine Learning based Nutritional assistant using Convolution-al Neural Network |
| Authors Name: | Ranjeesh R , Ravikumar P , Vijayaprabu R , Vishnu V , Jaipriya S |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJNRD_188645
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| Published Paper Id: | IJNRD2303158 |
| Published In: | Volume 8 Issue 3, March-2023 |
| DOI: | |
| Abstract: | The nutrition assistant system proposed in the study is a technology-based solution to help individuals make healthier dietary choices. The system uses advanced machine learning techniques, specifically a convolution-al neural network (CNN), to accurately identify food items from images taken by the user's smartphone camera. The CNN model was trained on a large dataset of food images to ensure accurate identification of food items. The diet plan application integrated with the CNN model allows users to set their health goals and dietary preferences, such as vegetarian or gluten-free diets. Based on this information, the system provides personalized dietary recommendations and meal plans that meet the user's nutritional needs. The system not only identifies food items but also estimates portion sizes of the foods in the image, which is used to provide more accurate nutrient content information and track the user's daily caloric intake. The user study conducted to evaluate the system found that the system helped users make healthier food choices and understand their nutritional needs. The system's ability to provide personalized dietary recommendations was particularly valued by participants, who reported that it helped them better understand their nutritional needs and make more informed food choices. Overall, the nutrition assistant system has the potential to prevent diet-related health issues by providing tailored dietary recommendations that are specific to each individual's health goals and dietary preferences. |
| Keywords: | Nutrional Assistant, Diet Planning, Machine Learning, Neural Network |
| Cite Article: | "Machine Learning based Nutritional assistant using Convolution-al Neural Network", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.8, Issue 3, page no.b485-b489, March-2023, Available :http://www.ijnrd.org/papers/IJNRD2303158.pdf |
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| ISSN: |
2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID:IJNRD2303158 Registration ID: 188645 Published In: Volume 8 Issue 3, March-2023 DOI (Digital Object Identifier): Page No: b485-b489 Country: Kanyakumari, Tamil Nadu, India Research Area: Information Technology Publisher : IJ Publication Published Paper URL : https://www.ijnrd.org/viewpaperforall?paper=IJNRD2303158 Published Paper PDF: https://www.ijnrd.org/papers/IJNRD2303158 |
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ISSN: 2456-4184
Impact Factor: 8.76 and ISSN APPROVED
Journal Starting Year (ESTD) : 2016
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