Estimation of Non-Invasive Grape Ripeness and Sweetness from Images Captured by a General-Purpose Camera-Reference-Cited by-同舟云学术

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Estimation of Non-Invasive Grape Ripeness and Sweetness from Images Captured by a General-Purpose Camera

Published:2023-11-06 Issue: Volume: Page:295-300
ISSN:
Container-title:2023 IEEE International Workshop on Metrology for Agriculture and Forestry (MetroAgriFor)
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Author:

Leow Chee Siang¹,Shimazu Ryosuke¹,Kitagawa Tomoki¹,Yajima Hideaki¹,Buayai Prawit¹,Makino Koji¹,Mao Xiaoyang¹,Nishizaki Hiromitsu¹

Affiliation:

1. University of Yamanashi,Kofu,Japan

Funder

Bio-oriented Technology Research Advancement Institution

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10424027/10424015/10424087.pdf?arnumber=10424087

Reference25 articles.

1. Evaluation of Table Grape Flavor Based on Deep Neural Networks

2. An Autonomous Grape-Harvester Robot: Integrated System Architecture

3. End-to-End Automatic Berry Counting for Table Grape Thinning

4. Supporting table grape berry thinning with deep neural network and augmented reality technologies

5. Computer Vision and Deep Learning for Precision Viticulture

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Review on Application of Vision Transformers in IoT Edge Devices for Plant Sensor Measurement Forecasting;2024 IEEE 11th Workshop on Advances in Information, Electronic and Electrical Engineering (AIEEE);2024-05-31

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