Automated diagnosis of diverse coffee leaf images through a stage-wise aggregated triple deep convolutional neural network-Reference-Cited by-同舟云学术

Automated diagnosis of diverse coffee leaf images through a stage-wise aggregated triple deep convolutional neural network

Published:2022-01 Issue:1 Volume:33 Page:
ISSN:0932-8092
Container-title:Machine Vision and Applications
language:en
Short-container-title:Machine Vision and Applications

Author:

Montalbo Francis Jesmar P.^ORCID

Publisher

Springer Science and Business Media LLC

Subject

Computer Science Applications,Computer Vision and Pattern Recognition,Hardware and Architecture,Software

Link

https://link.springer.com/content/pdf/10.1007/s00138-022-01277-y.pdf

Reference60 articles.

1. Mutandwa, E., Kanuma, N.T., Rusatira, E., Kwiringirimana, T., Mugenzi, P., Govere, I., Foti, R.: Analysis of coffee export marketing in Rwanda: application of the Boston consulting group matrix. Afr. J. Bus. Manage. 3(5), 210–219 (2009). https://doi.org/10.5897/AJBM09.009

2. Badel, J.L., Zambolim, L.: Coffee bacterial diseases: a plethora of scientific opportunities. Plant. Pathol. 68(3), 411–425 (2019). https://doi.org/10.1111/ppa.12966

3. Millard, E.: Still brewing: fostering sustainable coffee production. World Dev. Perspect. 7, 32–42 (2017). https://doi.org/10.1016/j.wdp.2017.11.004

4. LeCun, Y., Kavukcuoglu, K., Farabet, C.: Convolutional networks and applications in vision. In: Proceedings of 2010 IEEE International Symposium on Circuits and Systems, Paris, pp. 253–256 (2010). https://doi.org/10.1109/ISCAS.2010.5537907

5. LeCun, Y., Boser, B., Denker, J.S., Henderson, D., Howard, R.E., Hubbard, W., Jackel, L.D.: Handwritten digit recognition with a back-propagation network. In: Advances in Neural Information Processing Systems 2 (NIPS’89), pp. 396–404 (1990). https://papers.nips.cc/paper/1989/file/53c3bce66e43be4f209556518c2fcb54-Paper.pdf.

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