Apple Fruit Classification and Damage Detection Using Pre-trained Deep Neural Network as Feature Extractor-Reference-Cited by-同舟云学术

Apple Fruit Classification and Damage Detection Using Pre-trained Deep Neural Network as Feature Extractor

Published:2022 Issue: Volume: Page:235-243
ISSN:2367-3370
Container-title:Lecture Notes in Networks and Systems
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Author:

Kapila Gurucharan^ORCID,Vandana B.,Khaitan Ayush,Francis Avinash A.,Ajay Kumar C. H.

Publisher

Springer Singapore

Link

https://link.springer.com/content/pdf/10.1007/978-981-16-8512-5_26

Reference18 articles.

1. S. Naik, B. Patel, Machine vision based fruit classification and grading—a review. Int. J. Comput. Appl. 170(9) (2017)

2. M. Senthilarasi, S. Mohamed Mansoor Roomi, Particle swarm optimized fuzzy model for the classification of banana ripeness. IEEE Sens. J. 17(15) (2017)

3. D. Srivastava, R. Wadhvani, M. Gyanchandani, Color feature extraction methods for content based image retrieval, in 2016 International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET), 2016, pp. 2259–2263

4. Y. Zhang, S. Wang, G. Ji, P. Phillips, Fruit classification using computer vision and feedforward neural network. J. Food Eng. 143, 167–177

5. L. Yudong Zhang, Classification of fruits using computer vision and a multiclass support vector machine 12(9), 12489–12505 (2012)

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