최소 단어 이상 선택하여야 합니다.
최대 10 단어까지만 선택 가능합니다.
다음과 같은 기능을 한번의 로그인으로 사용 할 수 있습니다.
NTIS 바로가기한국산학기술학회논문지 = Journal of the Korea Academia-Industrial cooperation Society, v.22 no.5, 2021년, pp.7 - 14
김삼근 (한경대학교 컴퓨터응용수학부(컴퓨터시스템연구소)) , 안재근 (한경대학교 컴퓨터응용수학부(컴퓨터시스템연구소))
Tomato crops are highly affected by tomato diseases, and if not prevented, a disease can cause severe losses for the agricultural economy. Therefore, there is a need for a system that quickly and accurately diagnoses various tomato diseases. In this paper, we propose a system that classifies nine di...
Dheeb Al Bashish, Malik Braik and Sulieman Bani-Ahmad, "Detection and classification of leaf diseases using K-means-based segmentation and neural networks based classification," Inform Technol J 10, pp.267-275, 2011. DOI: https://doi.org/10.3923/itj.2011.267.275
Jayme Garcia Arnal Barbedo, "A review on the main challenges in automatic plant disease identification based on visible range images," Biosystems Engineering, Vol. 144, pp. 52-60, 2016. DOI: https://doi.org/10.1016/j.biosystemseng.2016.01.017.
Alireza Khoshroo, Arman Arefi, and Jalal Khodaei, "Detection of Red Tomato on Plants using Image Processing Techniques," Agricultural Communications, 2, pp.9-15, 2014. https://www.researchgate.net/publication/267624601_Detection_of_Red_Tomato_on_Plants_using_Image_Processing_Techniques
David Ireri, Eisa Belal, Cedric Okinda, Nelson Makange, and Changying Ji, "A computer vision system for defect discrimination and grading in tomatoes using machine learning and image processing," Artificial Intelligence in Agriculture, Volume 2, pp.28-37, 2019. DOI: https://doi.org/10.1016/j.aiia.2019.06.001
Dong Pixia, Wang Xiangdong, "Recognition of Greenhouse Cucumber Disease Based on Image Processing Technology," Open Journal of Applied Sciences, 3, pp.27-31, 2013. DOI: https://doi.org/10.4236/ojapps.2013.31B006
Tejal Deshpande, Sharmila Sengupta and K.S.Raghuvanshi, "Grading and Identification of Disease in Pomegranate Leaf and Fruit", (IJCSIT) International Journal of Computer Science and Information Technologies, Vol. 5 (3), pp. 4638-4645, 2014. http://www.ijcsit.com/docs/Volume%205/vol5issue03/ijcsit20140503429.pdf
Arpan Singh Rajput, Shailja Shukla, and S. S. Thakur, "Soybean Leaf Diseases Detection and Classification Using Recent Image Processing Techniques," International Journal of Students' Research in Technology & Management eISSN: 2321-2543, Vol 8, No 3, pp 01-08, 2020. DOI: https://doi.org/10.18510/ijsrtm.2020.831
Bin Liu, Yun Zhang, DongJian He, and Yuxiang Li, "Identification of apple leaf diseases based on deep convolutional neural networks," Symmetry, 10, 2018. DOI: https://doi.org/10.3390/sym10010011
Mohammed Brahimi, Boukhalfa Kamel, and Abdelouahab Moussaoui, "Deep Learning for Tomato Diseases: Classification and Symptoms Visualization," Applied Artificial Intelligence 31(4), pp. 299-315, 2017. DOI:: http://dx.doi.org/10.1080/08839514.2017.1315516
Sharada P. Mohanty, David P. Hughes, and Marcel Salathe, "Using Deep Learning for Image-Based Plant Disease Detection," Frontiers in Plant Science, vol. 7, pp.1-10, 2016. DOI: https://doi.org/10.3389/fpls.2016.01419
Jose A. Jimenez-Berni, Amanda Ramcharan, and Jayme G. Barbedo, "Convolutional Neural Networks for the Automatic Identification of Plant Diseases," Frontiers in Plant Science, vol. 10: 941, 2019. DOI: https://doi.org/10.3389/fpls.2019.00941
Aravind Krishnaswamy Rangarajan, Raja Purushothaman, and Aniirudh Ramesh, "Tomato crop disease classification using pre-trained deep learning algorithm," Procedia Computer Science, Volume 133, pp. 1040-1047, 2018. DOI: https://doi.org/10.1016/j.procs.2018.07.070.
Jiten Khurana, Anurag Sharma, Harshit Singh Chhabra, and Rahul Nijhawan, "An Integrated Deep Learning Framework of Tomato Leaf Disease Detection," International Journal of Innovative Technology and Exploring Engineering (IJITEE), Volume-8, Issue-11S, 2019. Available at: https://www.ijitee.org/wp-content/uploads/papers/v8i11S/K101009811S19.pdf
PlantVillage Dataset, https://www.kaggle.com/emmarex/plantdisease
Olga Russakovsky*, Jia Deng*, Hao Su, Jonathan Krause, Sanjeev Satheesh, Sean Ma, Zhiheng Huang, Andrej Karpathy, Aditya Khosla, Michael Bernstein, Alexander C. Berg and Li Fei-Fei (* equal contribution), "ImageNet Large Scale Visual Recognition Challenge", International Journal of Computer Vision(IJCV), Vol 115, Issue 3, pp. 211-252, 2015. http://www.image-net.org/challenges/LSVRC/
ImageNet. http://www.image-net.org
Arthur Flexer, "Statistical evaluation of neural networks experiments: Minimum requirements and current practice", In Proceedings of the 13th European Meeting on Cybernetics and Systems Research, volume 2, pp.1005-1008, Vienna, Austria, 1996. https://researchgate.net/publication/2627930_Statistical_Evaluation_of_Neural_Network_Experiments_Minimum_Requirements_and_Current_Practice.
*원문 PDF 파일 및 링크정보가 존재하지 않을 경우 KISTI DDS 시스템에서 제공하는 원문복사서비스를 사용할 수 있습니다.
Free Access. 출판사/학술단체 등이 허락한 무료 공개 사이트를 통해 자유로운 이용이 가능한 논문
※ AI-Helper는 부적절한 답변을 할 수 있습니다.