A Novel Method for Fruit Detection and Calorie Estimation using CNN

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Jyoti Chalikar
Meenakshi Sundaram

Abstract

Dietary food consumption has become significant these days as the patients need to deal with food admission without fail. Picture-based organic product calorie assessment is critical to different versatile applications for recording ordinary feast. In any case, some of them would need manual support for calories assessment, and regardless of whether it is computerized, organic product classifications are frequently restricted or pictures from numerous perspectives are required. It isn't yet accomplished to gauge organic product calorie with functional precision and assessing natural product calories from an organic product photograph is a perplexing issue. Along these lines, in this paper, we propose assessing natural product calorie from an organic product photograph by synchronous learning of organic product pictures and calories utilizing profound learning. We present a framework which can perceive the organic product picture, and afterward foresee its dietary substance, like calories. We would present CNN based ways to deal with these issues, with favourable primer outcomes.

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How to Cite
Jyoti Chalikar, & Meenakshi Sundaram. (2023). A Novel Method for Fruit Detection and Calorie Estimation using CNN. Journal of Advanced Zoology, 44(S6), 537–545. https://doi.org/10.17762/jaz.v44iS6.2253
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