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Jihyoung Ryu and Yeongmin Jang
Convolution neural networks have received much interest recently in the categorization of hyperspectral images (HSI). Deep learning requires a large number of labeled samples in order to optimize numerous parameters due to the expansion of architecture d...
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Yifan Si, Dawei Gong, Yang Guo, Xinhua Zhu, Qiangsheng Huang, Julian Evans, Sailing He and Yaoran Sun
DeepLab v3+ neural network shows excellent performance in semantic segmentation. In this paper, we proposed a segmentation framework based on DeepLab v3+ neural network and applied it to the problem of hyperspectral imagery classification (HSIC). The dim...
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Wei Wei, Jiatao Nie and Chunna Tian
Hyperspectral image (HSI) restoration is an important task of hyperspectral imagery processing, which aims to improve the performance of the subsequent HSI interpretation and applications. Considering HSI is always influenced by multiple factors?such as ...
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Danfeng Liu, Liguo Wang and Jón Atli Benediktsson
Most of the available hyperspectral image (HSI) visualization methods can be considered as data-oriented approaches. These approaches are based on global data, so it is difficult to optimize display of a specific object. Compared to data-oriented approac...
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Can Cui, Ying Li, Bingxin Liu and Guannan Li
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Haixia Jin, Jingjing Peng, Rutian Bi, Huiwen Tian, Hongfen Zhu and Haoxi Ding
Mapping soil organic carbon (SOC) accurately is essential for sustainable soil resource management. Hyperspectral data, a vital tool for SOC mapping, is obtained through both laboratory and satellite-based sources. While laboratory data is limited to sam...
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Bethany Melville, Arko Lucieer and Jagannath Aryal
This paper presents the results of a study undertaken to classify lowland native grassland communities in the Tasmanian Midlands region. Data was collected using the 20 band hyperspectral snapshot PhotonFocus sensor mounted on an unmanned aerial vehicle....
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Bethany Melville, Arko Lucieer and Jagannath Aryal
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Zahra Dabiri and Stefan Lang
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Joongbin Lim, Kyoung-Min Kim and Ri Jin
Remote sensing (RS) has been used to monitor inaccessible regions. It is considered a useful technique for deriving important environmental information from inaccessible regions, especially North Korea. In this study, we aim to develop a tree species cla...
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Graham Ferrier, Athanassios Ganas, Richard Pope and A. Jo Miles
A Mineral prospectivity mapping (MPM) approach using a GIS-based weighted linear combination implementation of a Multi-Criteria Evaluation approach utilising a fuzzy Analytical Hierarchy Process to elucidate expert knowledge has been implemented to analy...
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Luyan Ji, Xiurui Geng, Kang Sun, Yongchao Zhao and Peng Gong
Extracting surface water distribution with satellite imagery has been an important subject in remote sensing. Spectral indices of water only use information from a limited number of bands, thus they may have poor performance from pixels contaminated by i...
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María Gema Carrasco-García, María Inmaculada Rodríguez-García, Juan Jesús Ruíz-Aguilar, Lipika Deka, David Elizondo and Ignacio José Turias Domínguez
Hyperspectral technology has been playing a leading role in monitoring oil spills in marine environments, which is an issue of international concern. In the case of monitoring oil spills in local areas, hyperspectral technology of small dimensions is the...
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Lukas Wiku Kuswidiyanto, Dong Eok Kim, Teng Fu, Kyoung Su Kim and Xiongzhe Han
The cultivation of kimchi cabbage in South Korea has always faced significant challenges due to the looming presence of Alternaria leaf spot (ALS), which is a fungal disease mainly caused by Alternaria alternata. The emergence of black spots resulting fr...
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Shiuan Wan, Mei-Ling Yeh and Hong-Lin Ma
Generation of a thematic map is important for scientists and agriculture engineers in analyzing different crops in a given field. Remote sensing data are well-accepted for image classification on a vast area of crop investigation. However, most of the re...
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J. Pablo Arroyo-Mora, Margaret Kalacska, Deep Inamdar, Raymond Soffer, Oliver Lucanus, Janine Gorman, Tomas Naprstek, Erica Skye Schaaf, Gabriela Ifimov, Kathryn Elmer and George Leblanc
Hyperspectral remote sensing provides a wealth of data essential for vegetation studies encompassing a wide range of applications (e.g., species diversity, ecosystem monitoring, etc.). The development and implementation of UAV-based hyperspectral systems...
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Dirk Aurin, Antonio Mannino and David J. Lary
A Global Ocean Carbon Algorithm Database (GOCAD) has been developed from over 500 oceanographic field campaigns conducted worldwide over the past 30 years including in situ reflectances and coincident satellite imagery, multi- and hyperspectral Chromopho...
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Morena Gale?ic Divic, Marija Kvesic Ivankovic, Vladimir Divic, Mak Ki?evic, Marko Panic, Predrag Lugonja, Vladimir Crnojevic and Roko Andricevic
Water quality monitoring in coastal areas and estuaries poses significant challenges due to the intricate interplay of hydrodynamic, chemical, and biological processes, regardless of the chosen monitoring methods. In this study, we analyzed the applicabi...
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