Identification of External Defects on Fruits Using Deep Learning-Reference-Cited by-同舟云学术

Identification of External Defects on Fruits Using Deep Learning

Published:2022 Issue: Volume: Page:565-575
ISSN:0302-9743
Container-title:Pattern Recognition and Image Analysis
language:
Short-container-title:

Author:

Aguiar Henrique Tavares^ORCID,Vasconcelos Raimundo C. S.^ORCID

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-04881-4_45

Reference11 articles.

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2. Capizzi, G., Sciuto, G., Napoli, C., Tramontana, E., Woźniak, M.: A novel neural networks-based texture image processing algorithm for orange defects classification. Int. J. Comput. Sci. Appl. 13, 45–60 (2016)

3. Devi, P., Vijayarekha, K.: Machine vision applications to locate fruits, detect defects and remove noise: a review. Rasayan J. Chem. 7, 104–113 (2014)

4. Dubey, S.R., Jalal, A.S.: Adapted approach for fruit disease identification using images. Int. J. Comput. Vis. Image Processing (IJCVIP) 2, 44–58 (2012). https://doi.org/10.4018/ijcvip.2012070104

5. Haralick, R.M., Shanmugam, K., Dinstein, I.: Textural features for image classification. IEEE Trans. Syst. Man Cybern. SMC 3(6), 610–621 (1973). https://doi.org/10.1109/TSMC.1973.4309314

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