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  Published Paper Details:

  Paper Title

COMPUTER VISION BASED FOOD RECOGNITION WITH NUTRITION ANALYSIS

  Authors

  LAKSHMI S,  SHALINI K GOWDA,  G S SUCHITHA,  DARSHAN GOWDA TS

  Keywords

Convolutional Neural Network, Deep Learning, IoU, Machine Learning, R-CNN

  Abstract


Computer vision based food recognition is a technology that uses machine learning algorithms to identify and classify different types of food in digital images or videos. This technology has a wide range of applications, including dietary analysis and tracking, nutrition labelling, and food safety. One of the key benefits of food recognition is the ability to automatically extract nutritional information from food images. This can be particularly useful for individuals who are trying to maintain a healthy diet, as it allows them to easily track their daily caloric intake and ensure that they are getting the necessary nutrients. There are several different approaches to food recognition, including using machine learning algorithms to analyse images of food, using pattern recognition techniques to identify specific features of different types of food, and using deep learning techniques to classify images based on their visual characteristics. Overall, computer vision based food recognition has the potential to revolutionize the way we think about food and nutrition, and could have a significant impact on public health.

  IJCRT's Publication Details

  Unique Identification Number - IJCRT2301042

  Paper ID - 229553

  Page Number(s) - a339-a345

  Pubished in - Volume 11 | Issue 1 | January 2023

  DOI (Digital Object Identifier) -   

  Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882

  E-ISSN Number - 2320-2882

  Cite this article

  LAKSHMI S,  SHALINI K GOWDA,  G S SUCHITHA,  DARSHAN GOWDA TS,   "COMPUTER VISION BASED FOOD RECOGNITION WITH NUTRITION ANALYSIS", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.11, Issue 1, pp.a339-a345, January 2023, Available at :http://www.ijcrt.org/papers/IJCRT2301042.pdf

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ISSN: 2320-2882
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Journal Starting Year (ESTD) : 2013
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ISSN and 7.97 Impact Factor Details


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ISSN
ISSN: 2320-2882
Impact Factor: 7.97 and ISSN APPROVED
Journal Starting Year (ESTD) : 2013
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