Development of a Non-Destructive Fruit Quality Predictor Using Convolutional Neural Network Regression Model on Raspberry Pi
The rapid progress in agriculture continually increases the demand for high-quality fruits. However, the quality of the fruits was usually assessed by a destructive method that normally led to a concern that this traditional approach is time-consuming and prone to human mistakes. To address these pr...
| Published in: | 2022 2nd International Conference on Emerging Smart Technologies and Applications, eSmarTA 2022 |
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| Main Author: | |
| Format: | Conference paper |
| Language: | English |
| Published: |
Institute of Electrical and Electronics Engineers Inc.
2022
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| Online Access: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85142453203&doi=10.1109%2feSmarTA56775.2022.9935374&partnerID=40&md5=53ece948982f8d47cdc52f5cdeed9c9d |