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International Journal of Advanced Research in Computer and Communication Engineering A monthly Peer-reviewed & Refereed journal
ISSN Online 2278-1021ISSN Print 2319-5940Since 2012
IJARCCE adheres to the suggestive parameters outlined by the University Grants Commission (UGC) for peer-reviewed journals, upholding high standards of research quality, ethical publishing, and academic excellence.
← Back to VOLUME 12, ISSUE 4, APRIL 2023

FOOD IMAGE RECOGNITION FOR INVENTORY TALLY: A SURVEY

Bhrungeesh C, Chiranth M, Deepak N, Fardeen Ahmed Mansur

DOI: 10.17148/IJARCCE.2023.12450

Abstract: Food image recognition for inventory tally is a technology that allows for the automated identification and quantification of food items in a given inventory using image recognition algorithms. By analyzing images of food items and comparing them to a database of known food items, the system is able to accurately identify and count the number of each type of food present in the inventory. This technology has the potential to greatly improve the efficiency and accuracy of inventory management in food-related industries, such as restaurants, supermarkets, and food distribution centers. It can also potentially be used to help with food waste reduction efforts by allowing for more accurate tracking of expiration dates and helping to ensure that all food items are used before they go bad.

Keywords: CNN, Object Detection, Food Detection, Inventory Tally, Deep Learning.

How to Cite:

[1] Bhrungeesh C, Chiranth M, Deepak N, Fardeen Ahmed Mansur, “FOOD IMAGE RECOGNITION FOR INVENTORY TALLY: A SURVEY,” International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE), DOI: 10.17148/IJARCCE.2023.12450