Open Access
| Issue |
BIO Web Conf.
Volume 85, 2024
3rd International Conference on Research of Agricultural and Food Technologies (I-CRAFT-2023)
|
|
|---|---|---|
| Article Number | 01028 | |
| Number of page(s) | 6 | |
| Section | Research of Agricultural and Food Technologies | |
| DOI | https://doi.org/10.1051/bioconf/20248501028 | |
| Published online | 09 January 2024 | |
- Y. Yuan, Z. Yang, H. Liu, H. Wang, J. Li, L. Zhao. Infrared Physics & Technology, 127, p. 104442 (2022) [CrossRef] [Google Scholar]
- Z. Ünal, H. Aktaş. Classification of hazelnut kernels with deep learning, Postharvest Biology and Technology, 197, p. 112225 (2023) [Google Scholar]
- Z. Ünal, T. Kızıldeniz. Smart agriculture practices in potato production, Potato Production Worldwide, Academic Press, pp. 317-329 (2023) [Google Scholar]
- Y. Gulzar, Z. Ünal, H. Aktaş, M. S. Mir, Agriculture, 13, 8, p. 1479 (2023) [CrossRef] [Google Scholar]
- F. Sahlan, F. Hamidi, M. Z. Misrat, M. H. Adli, S. Wani, Y. Gulzar. International Journal on Perceptive and Cognitive Computing, 7, 1, 85-91 (2021) [Google Scholar]
- S. A. Khan, Y. Gulzar, S. Turaev, Y. S. Peng. Symmetry, 13, 11, p. 1987 (2021) [CrossRef] [Google Scholar]
- S. Alam, P. Raja, Y. Gulzar. Wireless Communications and Mobile Computing, p. 2022 (2022) [Google Scholar]
- Z. Du, X. Zeng, X. Li, X. Ding, J. Cao, W. Jiang. Trends in Food Science & Technology, 99, 133-141 (2020) [CrossRef] [Google Scholar]
- S. Fan, X. Liang, W. Huang, V. J. Zhang, Q. Pang, X. He, L. Li, C. Zhang. Computers and Electronics in Agriculture, 193, p. 106715 (2022) [CrossRef] [Google Scholar]
- D. P. Ariana, R. Lu, D. E. Guyer. Computers and electronics in agriculture, 53(1), 60-70 (2006) [CrossRef] [Google Scholar]
- P. Baranowski, W. Mazurek, J. Pastuszka-Woźniak. Postharvest Biology and Technology, 86, 249-258 (2013) [CrossRef] [Google Scholar]
- W.H. Lee, M.S. Kim, H. Lee, S.R. Delwiche, H. Bae, D.Y. Kim, B.K. Cho. Journal of Food Engineering, 130, 1-7 (2014) [CrossRef] [Google Scholar]
- J.C. Keresztes, E. Diels, M. Goodarzi, N. Nguyen-Do-Trong, P. Goos, B. Nicolai, W. Saeys. Postharvest biology and technology, 130, 103-115 (2017) [CrossRef] [Google Scholar]
- Z. Ünal, T. Kızıldeniz, M. Özden, H. Aktaş, Classification of red apple varieties with deep learning models. IV. International Turkic World Congress on Science and Engineering, Niğde, (2022) [Google Scholar]
- H. Aktaş, T. Kızıldeniz, Z. Ünal. Journal of Food Measurement and Characterization, 16, 3, 1983-1996 (2022) [CrossRef] [Google Scholar]
- C. Swathi, B.K. Anoop, D.A.S. Dhas, S.P. Sanker, Comparison of different image preprocessing methods used for retinal fundus images. In 2017 Conference on Emerging Devices and Smart Systems (ICEDSS) (2017) [Google Scholar]
- R. Chityala, S. Pudipeddi, Image processing and acquisition using Python., Abingdon, UK: CRC Press (2020) [CrossRef] [Google Scholar]
- Z. Li, X. Fang, G. Yang. Displays, 73, p. 102143 (2022) [CrossRef] [Google Scholar]
- P. Vasuki, J. Kanimozhi, M.B. Devi. A survey on image preprocessing techniques for diverse fields of medical imagery. In 2017 IEEE International Conference on Electrical, Instrumentation and Communication Engineering (ICEICE) (2017) [Google Scholar]
- D. Vijayalakshmi, M.K. Nath, O.P. Acharya. Sensing and Imaging, 21, 1, 40 (2020) [CrossRef] [Google Scholar]
- S. Adatrao, M. Mittal, An analysis of different image preprocessing techniques for determining the centroids of circular marks using hough transform. In 2016 2nd International Conference on Frontiers of Signal Processing (ICFSP) (2016) [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.