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作 者:Kamlesh Golhani Siva K.Balasundram Ganesan Vadamalai Biswajeet Pradhan
机构地区:[1]Department of Agriculture Technology,Faculty of Agriculture,Universiti Putra Malaysia,43400 Serdang,Selangor,Malaysia [2]Department of Plant Protection,Faculty of Agriculture,Universiti Putra Malaysia,43400 Serdang,Selangor,Malaysia [3]School of Systems,Management and Leadership,Faculty of Engineering and IT,University of Technology Sydney,Broadway,NSW 2007,Australia
出 处:《Information Processing in Agriculture》2018年第3期354-371,共18页农业信息处理(英文)
摘 要:This paper reviews advanced Neural Network(NN)techniques available to process hyperspectral data,with a special emphasis on plant disease detection.Firstly,we provide a review on NN mechanism,types,models,and classifiers that use different algorithms to process hyperspectral data.Then we highlight the current state of imaging and nonimaging hyperspectral data for early disease detection.The hybridization of NNhyperspectral approach has emerged as a powerful tool for disease detection and diagnosis.Spectral Disease Index(SDI)is the ratio of different spectral bands of pure disease spectra.Subsequently,we introduce NN techniques for rapid development of SDI.We also highlight current challenges and future trends of hyperspectral data.
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