Mixing supervised and unsupervised learning algorithms to solve human perception subjectivity in internal fruit quality assessment-Reference-Cited by-同舟云学术

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Mixing supervised and unsupervised learning algorithms to solve human perception subjectivity in internal fruit quality assessment

Published:2023-11-06 Issue: Volume: Page:337-342
ISSN:
Container-title:2023 IEEE International Workshop on Metrology for Agriculture and Forestry (MetroAgriFor)
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Author:

Piani Mirko¹,Bortolotti Gianmarco¹,Mengoli Dario²,Raule Niccolò¹,Spinelli Francesco¹,Manfrini Luigi¹

Affiliation:

1. University of Bologna,Department of Agricultural and Food Sciences (DISTAL),Bologna,Italy

2. University of Bologna,Department of Electrical, Electronic, and Information Engineering (DEI),Bologna,Italy

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10424027/10424015/10424353.pdf?arnumber=10424353

Reference17 articles.

1. Improving quality inspection of food products by computer vision––a review

2. Machine Vision-Based Measurement Systems for Fruit and Vegetable Quality Control in Postharvest

3. Current understanding and use of quality characteristics of horticulture products

4. Pigments in the Fruit of Red-Fleshed Kiwifruit (Actinidia chinensis and Actinidia deliciosa)

5. Application of a sensory-instrumental tool to study apple texture characteristics shaped by altitude and time of harvest

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