Fruit recognition from images using deep learning
Author:
Affiliation:
1. Faculty of Mathematics and Computer Science , Babeş-Bolyai University , Cluj-Napoca , Romania
2. Faculty of Exact Sciences and Engineering , “1 Decembrie 1918”University of Alba , Iulia, Alba Iulia , Romania
Abstract
Publisher
Walter de Gruyter GmbH
Link
https://www.sciendo.com/pdf/10.2478/ausi-2018-0002
Reference33 articles.
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2. [2] S. Bargoti, J. Underwood, Deep fruit detection in orchards, IEEE International Conference on Robotics and Automation (ICRA), 2017, pp. 3626–3633. ⇒28
3. [3] R. Barth, J. Ijsselmuiden, J. Hemming, E. Van Henten, Data synthesis methods for semantic segmentation in agriculture: A Capsicum annuum dataset, Computers and Electronics in Agriculture144 (2018) 284–296. ⇒29
4. [4] T. F. Chan, L. Vese, Active contours without edges. IEEE Trans. Image Process10, (2001) 266–277. ⇒29
5. [5] H. Cheng, L. Damerow, Y. Sun, M. Blanke, Early yield prediction using image analysis of apple fruit and tree canopy features with neural networks, Journal of Imaging, 3, 1 (2017) 6. ⇒29
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