Palm Fruit Ripeness Detection and Classification Using Various YOLOv8 Models-Reference-Cited by-同舟云学术

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Palm Fruit Ripeness Detection and Classification Using Various YOLOv8 Models

Published:2023-10-17 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE 9th International Conference on Smart Instrumentation, Measurement and Applications (ICSIMA)
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Author:

Gunawan Teddy Surya¹,Kartiwi Mira²,Mansor Hasmah¹,Yusoff Nelidya Md.³

Affiliation:

1. International Islamic University Malaysia,Electrical and Computer Engineering Department,Kuala Lumpur,Malaysia,53100

2. International Islamic University Malaysia,Information Systems Department,Kuala Lumpur,Malaysia,53100

3. Universiti Teknologi Malaysia Kuala Lumpur,Razak Faculty of Technology and Informatics,Kuala Lumpur,Malaysia,54100

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10373396/10373418/10373435.pdf?arnumber=10373435

Reference10 articles.

1. Improving Sustainability of Palm Oil Production by Increasing Oil Extraction Rate: a Review

2. Oil palm fruit image ripeness classification with computer vision using deep learning and visual attention;Herman;Journal of Telecommunication, Electronic and Computer Engineering (JTEC),2020

3. Image-based processing for ripeness classification of oil palm fruit

4. Oil Palm Fresh Fruit Bunch Ripeness Detection Methods: A Systematic Review

5. Fruit Battery Method for Oil Palm Fruit Ripeness Sensor and Comparison with Computer Vision Method

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