ADVANCED FRUIT, VEGETABLE SCANNER AND BILL GENERATION USING YOLOv4 MODEL
Deveshwaran Sridharan
, Jerry Allen. M , Aravind. S , Lokeshwar. D. K , K.M.R Gurucharan
Computer vision; Yolo v4; Faster RCNN ; Deep learning; Object Detection; Real time recognition
Develop a scanner which uses tensorflow to learn about different vegetables or fruits and able to identify them. The goal of this project is to avoid barcode sticker on vegetable or fruits which may get damaged due to environment factor also injuries to health. To achieve this machine learning is used to train the machine to identify different fruits and vegetables. Also since this connects to the system the machine will identify the object and with their weight and calculate the bill using the provided metric system (which is customizable). It can prevent the wastage which is used in packaging these groceries, also we can buy the required amount of product, also since most of the software is open source the software is budget-friendly.
"ADVANCED FRUIT, VEGETABLE SCANNER AND BILL GENERATION USING YOLOv4 MODEL", TIJER - TIJER - INTERNATIONAL RESEARCH JOURNAL (www.TIJER.org), ISSN:2349-9249, Vol.11, Issue 2, page no.614-621, February-2024, Available :https://tijer.org/TIJER/papers/TIJERB001097.pdf
Volume 11
Issue 2,
February-2024
Pages : 614-621
Paper Reg. ID: TIJER_151042
Published Paper Id: TIJERB001097
Downloads: 000277
Research Area: Science and Technology
Country: Thiruvallur,Chennai, Tamil Nadu, India
ISSN: 2349-9249 | IMPACT FACTOR: 8.57 Calculated By Google Scholar | ESTD YEAR: 2014
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.57 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: TIJER (IJ Publication) Janvi Wave
