Spectroscopy and Spectral Analysis, Volume. 43, Issue 5, 1550(2023)
Hyperspectral Data Analysis for Classification of Soybean Leaf Diseases
[1] [1] Chapwanya M, Matusse A, Dumont Y. Applied Mathematical Modelling, 2021, 90: 912.
[2] [2] Wu F, Geng Y, Zhang Y Q, et al. Journal of Cleaner Production, 2020, 244: 119006.
[3] [3] Butler S, Kelly H, Mueller T, et al. Crop Protection, 2018, 112: 149.
[4] [4] Bock C H, Barbedo J G A, Del Ponte E M, et al. Phytopathology Research, 2020, 2(1): 1.
[5] [5] Xie C Q, Shao Y N, Li X L. Scientific Reports, 2015, 5: 16564.
[6] [6] Wang C Y, Linderholm H W, Song Y L, et al. International Journal of Environmental Research and Public Health, 2020, 17(7): 2459.
[7] [7] Zhang S L, Huang J L, Hanan J, et al. Multimedia Tools and Applications-An International Journal, 2020, 79(23-24): 16645.
[8] [8] Junges A H, Almance M A K, Fajardo T V M, et al. Tropical Plant Pathology. 2020, 45(5): 522.
[10] [10] Lu Z J, Ehsani R, Shi Y Y, et al. Scientific Reports, 2018, 8(1): 2793.
[11] [11] Tang R N, Chen X P, Li C. Applied Spectroscopy, 2018, 72(5): 740.
[12] [12] Daughtry C S T, Walthall C L, Kim M S, et al. Remote Sensing of Environment. 2010, 74(2): 229.
[13] [13] El-Hendawy S, Al-Suhaibani N, Hassan W, et al. PLOS ONE, 2017, 12(8): e0183262.
Get Citation
Copy Citation Text
LIU Shuang, YU Hai-ye, SUI Yuan-yuan, KONG Li-juan, YU Zhan-dong, GUO Jing-jing, QIAO Jian-lei. Hyperspectral Data Analysis for Classification of Soybean Leaf Diseases[J]. Spectroscopy and Spectral Analysis, 2023, 43(5): 1550
Received: Apr. 1, 2022
Accepted: --
Published Online: Jan. 7, 2024
The Author Email: