Collaborative representation of convolutional neural network features to detect artificial ripening of banana using multispectral imaging-Reference-Cited by-同舟云学术

Collaborative representation of convolutional neural network features to detect artificial ripening of banana using multispectral imaging

Published:2022-07-11 Issue:10 Volume:46 Page:
ISSN:0145-8892
Container-title:Journal of Food Processing and Preservation
language:en
Short-container-title:Food Processing Preservation

Author:

Vetrekar Narayan¹^ORCID,Prabhu Anish K.¹,Naik Aparajita²,Ramachandra Raghavendra³,Raja Kiran B.³,Desai Adavi R.⁴,Gad Rajendra S.¹

Affiliation:

1. School of Physical and Applied Sciences Goa University Goa India

2. Department of Bioengineering University of California Berkeley California USA

3. Faculty of Information Technology and Electrical Engineering, NTNU Gjøvik Norway

4. Horticultural Science, ICAR Old‐Goa India

Publisher

Hindawi Limited

Subject

General Chemical Engineering,General Chemistry,Food Science

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/jfpp.16882

Reference30 articles.

1. Evaluation of the effect of calcium carbide on induce ripening of Banana, pawpaw and mango cultivated within Kaduna Metropolis, Nigeria;Adeyemi M. M. H.;Journal of Chemical Society of Nigeria,2018

2. An overview on thermal image processing;Ansari S.;In,2017

3. Food adulteration: Sources, health risks, and detection methods

4. Distance Metric Learned Collaborative Representation Classifier(DML-CRC)

5. Identification of the species origin of commercially available processed food products by mitochondrial DNA analysis;Chandrika M.;International Food Research Journal,2010

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2. Multilevel Fusion of Multispectral Images to Detect the Artificially Ripened Banana;IEEE Sensors Letters;2023-01