Current State of Hyperspectral Remote Sensing for Early Plant Disease Detection: A Review
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TLDR
In this paper , the authors present modern advances in early plant disease detection based on hyperspectral remote sensing, identifying current gaps in the methodologies of experiments and a further direction for experimental methodological development is indicated.Abstract:
The development of hyperspectral remote sensing equipment, in recent years, has provided plant protection professionals with a new mechanism for assessing the phytosanitary state of crops. Semantically rich data coming from hyperspectral sensors are a prerequisite for the timely and rational implementation of plant protection measures. This review presents modern advances in early plant disease detection based on hyperspectral remote sensing. The review identifies current gaps in the methodologies of experiments. A further direction for experimental methodological development is indicated. A comparative study of the existing results is performed and a systematic table of different plants’ disease detection by hyperspectral remote sensing is presented, including important wave bands and sensor model information.read more
Citations
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Air Pollution Detection Using a Novel Snap-Shot Hyperspectral Imaging Technique
TL;DR: In this article , a large-scale, low-cost solution for detecting air pollution by combining hyperspectral imaging (HSI) technology and deep learning techniques was proposed by combining 3D Convolutional Neural Network Auto Encoder and principal components analysis (PCA) to find the optical properties of air pollution.
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Intelligent Identification of Early Esophageal Cancer by Band-Selective Hyperspectral Imaging
Tsung-Jung Tsai,A. G. Mukundan,Yucong Chi,Yu-Ming Tsao,Yao-Kuang Wang,Tsung‐Hsien Chen,I-Chen Wu,Chien Wei Huang,Hsiang-Chen Wang +8 more
TL;DR: The results of this investigation demonstrated that HSI contains a greater number of spectral characteristics than white-light imaging, which increases accuracy by roughly 5% and complies with NBI predictions.
Journal ArticleDOI
Early Detection of Bacterial Wilt in Tomato with Portable Hyperspectral Spectrometer
TL;DR: Wang et al. as discussed by the authors proposed a tomato BW detection model based on some optimal spectral features, including vegetation indexes and principal components (PCs), extracted by the sequential forward selection (SFS), the simulated annealing (SA), and were finally fed into the support vector machine (SVM) classifier to detect diseased tomatoes.
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Classification of Skin Cancer Using Novel Hyperspectral Imaging Engineering via YOLOv5
TL;DR: In this article , a dataset from the ISIC library was used to detect and classify skin cancer on the basis of basal cell carcinoma (BCC), squamous cell carcinomas (SCC), and seborrheic keratosis (SK).
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Plant Disease Diagnosis Using Deep Learning Based on Aerial Hyperspectral Images: A Review
TL;DR: In this paper , the authors provide an overview of the literature on hyperspectral remote sensing (HRS) for disease detection based on deep learning algorithms and further challenges and limitations regarding this topic are addressed.
References
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