Food classification using Deep learning

Food classification using Deep learning

Registration ID: IJNRD_213761

Published ID: IJNRD2402217

DOI: Click Here to Get

Dhanush Jogi K , Monisha H M , Adarsha Dalavai S M , Manvith Dalli

Agriculture, Crop recommendation, Machine learning(ML), Predictive modeling.

Crop recommendation is a crucial aspect of agriculture, aiding farmers in making informed decisions for optimal yield and profitability. The comparative study of five machine learning algorithms—Logistic Regression, One-vs- All, Decision Trees, Bagging Classifier, and Random Forest— for crop recommendation. The study highlights the significance of crop recommendation in addressing the challenges faced by farmers, such as uncertain weather conditions, soil variability, and market demands. By leveraging machine learning techniques, accurate and efficient crop predictions can be made, aiding farmers in selecting the most suitable crops for their specific conditions. These findings offer insights into the suitability of different machine learning algorithms for crop recommendation. Agricultural stakeholders can leverage this knowledge to make informed decisions regarding the adoption of suitable algorithms for developing efficient crop recommendation systems using the website.

Published Paper   E-Certificate

"Food classification using Deep learning ", IJNRD - INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (www.IJNRD.org), ISSN:2456-4184, Vol.9, Issue 2, page no.c160-c165, February-2024, Available :https://ijnrd.org/papers/IJNRD2402217.pdf

Volume 9 Issue 2, February-2024

Pages : c160-c165

Paper Reg. ID: IJNRD_213761

Published Paper Id: IJNRD2402217

Downloads: 000121128

Research Area: Information Technology 

Country: Bangalore, Karnataka, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2402217.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2402217

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

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

Publisher: IJNRD (IJ Publication) Janvi Wave

This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition

Call For Paper - Volume 10 | Issue 8 | August 2025

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INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (IJNRD) aims to explore advances in research pertaining to applied, theoretical and experimental Technological studies. The goal is to promote scientific information interchange between researchers, developers, engineers, students, and practitioners working in and around the world. IJNRD will provide an opportunity for practitioners and educators of engineering field to exchange research evidence, models of best practice and innovative ideas.

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