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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM46683

Estimation of food Calorie Detection: A Systematic Literature Review

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM46683

Volume:

9 |

5 |

May 2025

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM46683

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

RHR

Rohith H R

[IS

[2]Spanditha I S

[D

[3]Srinidhi Desai

[AG

[4]Manjunath A G

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Abstract

Food calorie discovery has surfaced as a vital area of exploration due to the global rise in rotundity and associated health pitfalls. This review synthesizes advancements across four studies that work deep literacy, computer vision, and convolutional neural networks( CNNs) for accurate food recognition and calorie estimation. ways include Inception V3, ResNet, TensorFlow APIs, andmulti-task CNNs, showcasing advancements in food image bracket, volume estimation, and calorie calculation. These styles address challenges like different food donations and dataset variability, paving the way for practical operations in salutary monitoring and healthcare.

KEYWORDS

Food calorie discovery convolutional neural networks deep literacy image recognition TensorFlow multi-task literacy volume estimation

Cite This Article

Rohith H R, [2]Spanditha I S, [3]Srinidhi Desai, [4]Manjunath A G, "Estimation of food Calorie Detection: A Systematic Literature Review," International Journal of Scientific Research in Engineering and Management, vol. 9, no. 5, May 2025. https://doi.org/10.55041/IJSREM46683

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Publication Date

2/4/2025

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