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Hasan, Noraini, Ibrahim, Shafaf, Aqilah Azlan, Anis. (1400). Fish diseases detection using convolutional neural network (CNN). نشریه هنرهای کاربردی, 13(1), 1977-1984. doi: 10.22075/ijnaa.2022.5839
Noraini Hasan; Shafaf Ibrahim; Anis Aqilah Azlan. "Fish diseases detection using convolutional neural network (CNN)". نشریه هنرهای کاربردی, 13, 1, 1400, 1977-1984. doi: 10.22075/ijnaa.2022.5839
Hasan, Noraini, Ibrahim, Shafaf, Aqilah Azlan, Anis. (1400). 'Fish diseases detection using convolutional neural network (CNN)', نشریه هنرهای کاربردی, 13(1), pp. 1977-1984. doi: 10.22075/ijnaa.2022.5839
Hasan, Noraini, Ibrahim, Shafaf, Aqilah Azlan, Anis. Fish diseases detection using convolutional neural network (CNN). نشریه هنرهای کاربردی, 1400; 13(1): 1977-1984. doi: 10.22075/ijnaa.2022.5839

Fish diseases detection using convolutional neural network (CNN)

International Journal of Nonlinear Analysis and Applications
مقاله 164، دوره 13، شماره 1، خرداد 2022، صفحه 1977-1984    اصل مقاله (560.04 K)
نوع مقاله: Research Paper
شناسه دیجیتال (DOI): 10.22075/ijnaa.2022.5839
نویسندگان
Noraini Hasan* 1؛ Shafaf Ibrahim1؛ Anis Aqilah Azlan2
1Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA Cawangan Melaka (Kampus Jasin), 77300 Merlimau, Melaka, Malaysia
2Try Smart Bite Sdn Bhd, The Vertical Business Suite (A-28-07), Bangsar South, No 8, Jalan Kerinchi, 59200 Kuala Lumpur, Malaysia
تاریخ دریافت: 30 شهریور 1400،  تاریخ پذیرش: 08 آذر 1400 
چکیده
The fishing industry has become an important income source in the world. However, fish diseases are considered a serious problem among the fishermen as it tends to spread quickly through the water. In decades, fish diseases have been diagnosed manually by the naked eyes of experienced fish farmers. Despite being time-consuming since some lab works are required in determining the relevant microorganisms that cause the diseases, this classical method most often leads to an inaccurate and misleading result. Accordingly, a fast and inexpensive method is therefore important and desirable. Convolutional Neural Network (CNN) performance has recently been demonstrated in a variety of computer vision and machine learning problems. Thus, a study on fish diseases detection using CNN is proposed. A total of 90 images of healthy leaf and two types of fish diseases which are White spot and Red spot was tested. The application of CNN to a variety of testing datasets returned good detection accuracy at 94.44\%. It can be inferred that the CNN is relatively good in detecting and classifying the type of diseases among infected fishes. Regardless, a study with a better number of datasets could be done in the future to improve the detection performance.
کلیدواژه‌ها
Fish diseases؛ Detection؛ Classification؛ Convolutional Neural Network (CNN)
مراجع

[1] S. Albawi, T.A. Mohammed and S. Al-Zawi, Understanding of a convolutional neural network, 2017 Int. Conf. Engin. Technol. (2017) 1–6.

[2] J. Amara, B. Bouaziz and A. Algergawy, A deep learning-based approach for banana leaf diseases classification, BTW (Workshops), (2017) 79–88.

[3] H. Chakravorty, R. Paul and P. Das, Image processing technique to detect fish disease, Int. J. Comput. Sci. Secur. 9(2) (2015) 121–131.

[4] A.J. Dyck and U.R. Sumaila, Economic impact of ocean fish populations in the global fishery, J. Bioecon. 12 (2010) 227–243.

[5] M. Føre, K. Frank, T. Norton, E. Svendsen, J.A. Alfredsen, T. Dempster, H. Eguiraun, W. Watson, A. Stahl, L.M. Sunde, C. Schellewald, K. Skøien, M. Alver and D. Berckmans, Precision fish farming: A new framework to improve production in aquaculture, Biosyst. Engin. 173 (2018) 176–193.

[6] R. Harikrishnan, C. Balasundaram and M.S. Heo, Fish health aspects in grouper aquaculture, Aquaculture 320(1–2) (2011) 1–21.

[7] D. Kamilya and K.R. John, Epizootic ulcerative syndrome, P.T.K. Woo, J.A. Leong and K. Buchmann (eds), Climate Change Infect. Fish Diseases, CABI, (2020).

[8] V. Lyubchenko, R. Matarneh, V.L.O. Kobylin, Digital image processing techniques for detection and diagnosis of fish diseases, Int. J. Adv. Res. Comput. Sci. Software Engin. 6(7) (2016) 79–83.

[9] S. Malik, T. Kumar and A.K. Sahoo, Image processing techniques for identification of fish disease, IEEE 2nd Int. Conf. Signal Image Proces. 2017 (2017) 55–59.

[10] H. Mustafidah, Diagnosa penyakit ikan menggunakan sistem pakar, JUITA 1(4) (2011).

[11] S.N. Pauzi, M.G. Hassan, N. Yusoff, N.H. Harun, A.H. Abu Bakar and B.C. Kua, A review on image processing for fish disease detection, Asian Conference on Intelligent Computing and Data Sciences (ACIDS) 2021, J. Phys. Conf. Series 1997 (2021) 012042.

[12] P.K. Rao, Histopathological changes in the skin and gills of Channa punctatus due to bacterial infestation causes epizootic ulcerative syndrome (EUS), Int. J. Res. Appl. Natural Social Sci. 9(3) (2021) 29–36.

[13] A. Salman, S.A. Siddiqui, F. Shafait, A. Mian, M. Shortis, K. Khurshid, A. Ulges and U. Schwanecke, Automatic fish detection in underwater videos by a deep neural network-based hybrid motion learning system, ICES J. Marine Sci. 77(4) (2020) 1295–1307.

[14] W.E. Smith and E.J. Smith, Forensic Digital Image Processing: Opimization of Imression Evidanc, 1en Ed., CRC Press, 2018.

[15] J. Wu, Introduction to convolutional neural networks, National Key Lab for Novel Software Technol. Nanjing Univ. China 5(23) (2017) 1–31.

[16] X. Yang, S. Zhang, J. Liu, Q. Gao, S. Dong and C. Zhou, Deep learning for smart fish farming: Application, opportunities and challenges, Rev. Agricul. 13(1) (2021) 66–90.

[17] D. Zeldis and S. Prescott, Fish disease diagnosis program - problems and some solutions, Aquacul. Engin. 23(1–3) (2000) 3–11.

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