AI and CV based 2D-CNN algorithm: botanical authentication of Indian honey-Reference-Cited by-同舟云学术

AI and CV based 2D-CNN algorithm: botanical authentication of Indian honey

Published:2024 Issue: Volume: Page:
ISSN:2753-8095
Container-title:Sustainable Food Technology
language:en
Short-container-title:Sustainable Food Technol.

Author:

Brar Dilpreet Singh¹^ORCID,Aggarwal Ashwani Kumar²,Nanda Vikas¹,Saxena Sudhanshu³,Gautam Satyendra³⁴

Affiliation:

1. Department of Food Engineering and Technology, Sant Longowal Institute of Engineering and Technology, Longowal, 148106, Punjab, India

2. Department of Electrical and Instrumentation Engineering, Sant Longowal Institute of Engineering and Technology, Longowal, 148106, Punjab, India

3. Food Technology Division, Bhabha Atomic Research Centre, Trombay, Mumbai-85, India

4. Homi Bhabha National Institute, Anushaktinagar, Mumbai-94, India

Abstract

A deep learning framework based on the 2D-CNN model and an inexpensive and robust analysis methodology based on computer vision (CV) was used for the botanical authentication of Indian unifloral honey varieties.

Funder

Board of Research in Nuclear Sciences

Bhabha Atomic Research Centre

Publisher

Royal Society of Chemistry (RSC)

Link

http://pubs.rsc.org/en/content/articlepdf/2024/FB/D3FB00170A

Reference33 articles.

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2. Commission Delegated Regulation (EU) , PDO-PT-0268-AM01 relating to "Mel dos Açores" , Official Journal of the European Union C 384/16, 2019

3. Botanical authentication of lavender (Lavandula spp.) honey by a novel DNA-barcoding approach coupled to high resolution melting analysis

4. Food authentication: Techniques, trends & emerging approaches

5. A comprehensive review on unethical honey: Validation by emerging techniques

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