EDP Sciences logo
Web of Conferences logo
Search
Menu
All issues Volume 59 (2024) ITM Web Conf., 59 (2024) 03015 References
Open Access
Issue
ITM Web Conf.
Volume 59, 2024
II International Workshop “Hybrid Methods of Modeling and Optimization in Complex Systems” (HMMOCS-II 2023)
Article Number 03015
Number of page(s) 13
Section Data Mining, Machine Learning and Patern Recognition
DOI https://doi.org/10.1051/itmconf/20245903015
Published online 25 January 2024
  1. J. Lu, L. Tan, H. Jiang, Agriculture 11(8), 707 (2021) [CrossRef] [Google Scholar]
  2. N. Tariq, R. A. Hamzah, T. F. Ng, S. L. Wang, H. Ibrahim, IEEE Access 9, 87763–87776 (2021) [CrossRef] [Google Scholar]
  3. D. Blanco, P. Fernández, A. Fernández, B.J. Alvarez, J.C. Rico, Applied Sciences 11(1), 178 (2021) [Google Scholar]
  4. G. Wang, C. Lopez-Molina, B. De Baets, J. Math. Imaging Vision 61, 1096–1111 (2019) [CrossRef] [MathSciNet] [Google Scholar]
  5. C. Lopez-Molina, M. Galar, H. Bustince, B. De Baets, Pattern Recogn 47, 270–281 (2014) [CrossRef] [Google Scholar]
  6. S. Eser, A. Derya, Expert Syst. Appl 115, 499–511 (2019) [CrossRef] [Google Scholar]
  7. M. Bastan, S.S. Bukhari, T. Breuel, IET Image Proc 11, 1325–1332 (2017) [CrossRef] [Google Scholar]
  8. J. Yang, B. Price, S. Cohen, H. Lee, M.H. Yang, Object contour detection with a fully convolutional encoder-decoder network, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 193–202 (2016) [Google Scholar]
  9. J. Long, E. Shelhamer, T. Darrell, Fully convolutional networks for semantic segmentation, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 3431–3440 (2015) [Google Scholar]
  10. O.P. Verma, A.S. Parihar, IEEE Trans. Fuzzy Syst. 25, 114–127 (2016) [Google Scholar]
  11. S. Dhargupta, A. Chakraborty, S.K. Ghosal, S. Saha, R. Sarkar, Fuzzy edge detection based steganography using modified Gaussian distribution, Multimedia Tools Appl. 78, 17589–17606 (2019) [Google Scholar]
  12. I. Williams, N. Bowring, D. Svoboda, Comput. Vis. Image Underst. 122, 115–130. (2014) [CrossRef] [Google Scholar]
  13. Y. Liu, Z. Xie, H. Liu, IEEE Trans. Image Process. 29, 5206–5215 (2020) [CrossRef] [Google Scholar]
  14. S. Singh, R. Singh, Comparison of various edge detection techniques, 2015 2nd International Conference on Computing for Sustainable Global Development (INDIACom), New Delhi, India 393–396 (2015) [Google Scholar]
  15. M. Ansari, D. Kurchaniya, M. Dixit, International Journal of Multimedia and Ubiquitous Engineering 12, 1–12 (2017) [CrossRef] [Google Scholar]
  16. P. Podder, A.H.M.S. Parvez, M.N. Yeasmin, M.I. Khalil, Relative Performance Analysis of Edge Detection Techniques in Iris Recognition System, 2018 International Conference on Current Trends towards Converging Technologies (ICCTCT), Coimbatore, India 16, (2018) [Google Scholar]
  17. H. Miroslav, P. Kubinec, About Edge Detection in Digital Images. Radioengineering. (2018) [Google Scholar]
  18. A. Mohd, A. Zain, H. Haron, M. Azemin, M. Bahari, IOP Conference Series: Materials Science and Engineering 551, 012045. (2019) [CrossRef] [MathSciNet] [Google Scholar]
  19. G. Amer, A. Abushaala, Edge detection methods (2015) [Google Scholar]
  20. N. Mamatov, P. Sultanov, M. Jalelova, Sh. Tojiboeva, Eurasian Journal of Medical and Natural Sciences 3(9), 66–77 (2023) [Google Scholar]
  21. N.S. Mamatov, G.G. Pulatov, M.M. Jalelova, Digital Transformation and Artificial Intelligence 1(2), (2023) [Google Scholar]
  22. K. Ajay, D. Ghosh, Edge Detection via Edge-Strength Estimation Using Fuzzy Reasoning and Optimal Threshold Selection Using Particle Swarm Optimization, Advances in Fuzzy Systems 365817, 17 (2014) [Google Scholar]
  23. J. Sun, Image edge detection based on relative degree of grey incidence and Sobel operator, International Conference on Artificial Intelligence and Computational Intelligence, Springer, pp. 762–768 (2012) [Google Scholar]
  24. F. Gao, M. Wang, Y. Cai, S. Lu, Pattern Analysis and Applications 22, 1–14 (2019) [CrossRef] [MathSciNet] [Google Scholar]
  25. Sh. Fozilov, N. Mamatov, N. Niyozmatova, International Journal of Recent Technology and Engineering 8(2/11), 3784–3786 (2019) [Google Scholar]
  26. N.S. Mamatov, A.N. Samijonov, Y. Yuldoshev, R. Khusan, Selection the Informative Features on the Basis of Interrelationship of Features (Springer, Cham, 2020) [Google Scholar]
  27. N.S. Mamatov, B. Abdukadirov, Sh. Kakharov, B. Orifjonov, G. Abdukadirova, Peculiarities of face detection and recognition, 2021 International Conference on Information Science and Communications Technologies (ICISCT), Tashkent, Uzbekistan, pp. 1–5 (2021) [Google Scholar]
  28. N.S. Mamatov, B.A. Abdukadirov, A.N. Samijonov, B.N. Samijonov, Method for false attack detection in face identification system, 2021 International Conference on Information Science and Communications Technologies (ICISCT), Tashkent, Uzbekistan, pp. 1–4 (2021) [Google Scholar]
  29. P. Arbelaez, M. Maire, C. Fowlkes and J. Malik, IEEE TPAMI 33(5), 898–916 (2011). https://www2.eecs.berkeley.edu/Research/Projects/CS/vision/grouping/resources.html [CrossRef] [Google Scholar]
  30. Plant Leaves for Image Classification (2023). https://www.kaggle.com/datasets/csafrit2/plant-leaves-for-image-classification [Google Scholar]
  31. Rice Leaf Diseases Dataset (2023). https://www.kaggle.com/datasets/vbookshelf/rice-leaf-diseases [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.