Results 51 to 60 of about 4,082 (191)

Mapping Coastal Wetlands Using Transformer in Transformer Deep Network on China ZY1-02D Hyperspectral Satellite Images

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2022
Coastal wetlands mapping is a big challenge in remote sensing fields because of similar spectrum of different ground objects and their severe fragmentation and spatial heterogeneity.
Kai Liu, Weiwei Sun, Yijun Shao, Weiwei Liu, Gang Yang, Xiangchao Meng, Jiangtao Peng, Dehua Mao, Kai Ren   +8 more
doaj   +1 more source

Hyperspectral Imaging of Whole-Cell Region for Differentiating Cervical Squamous Intraepithelial Lesion Cytology. [PDF]

Cancer Med
We present here the effectiveness of hyperspectral imaging of Papanicolaou stained cells in the differential diagnosis between ASCs and other cell types. ABSTRACT Background Cervical cytology offers a relatively safe and reliable method for cancer screening, but the tests contain vague grading criteria, such as atypical squamous cells, and cannot ...
Matsukawa H, Yugawa K, Hosokawa C, Furuichi K, Kamada K, Tanabe K, Noriki S, Imamura Y, Naiki H, Inai K.   +9 more
europepmc   +2 more sources

Spectral-Spatial Offset Graph Convolutional Networks for Hyperspectral Image Classification

, 2021
In hyperspectral image (HSI) classification, convolutional neural networks (CNN) have been attracting increasing attention because of their ability to represent spectral-spatial features.
Minghua Zhang, Cheng Su, Haibin Mei, Hongling Luo, Wei Song   +4 more
core   +1 more source

Novel folded-PCA for improved feature extraction and data reduction with hyperspectral imaging and SAR in remote sensing

, 2014
As a widely used approach for feature extraction and data reduction, Principal Components Analysis (PCA) suffers from high computational cost, large memory requirement and low efficacy in dealing with large dimensional datasets such as Hyperspectral ...
Han, Junwei, Zabalza, Jaime, Yang, Mingqiang, Zhang, Yi, Ren, Jinchang, Marshall, Stephen, Wang, Jun   +6 more
core   +1 more source

Land use/land cover (LULC) classification using hyperspectral images: a review

Geo-spatial Information Science
In the rapidly evolving realm of remote sensing technology, the classification of Hyperspectral Images (HSIs) is a pivotal yet formidable task. Hindered by inherent limitations in hyperspectral imaging, enhancing the accuracy and efficiency of HSI ...
Chen Lou, Mohammed A. A. Al-qaness, Dalal AL-Alimi, Abdelghani Dahou, Mohamed Abd Elaziz, Laith Abualigah, Ahmed A. Ewees   +6 more
doaj   +1 more source

Semi-Supervised Classification for Hyperspectral Images Based on Multiple Classifiers and Relaxation Strategy

ISPRS International Journal of Geo-Information, 2018
Hyperspectral image (HSI) classification is a fundamental and challenging problem in remote sensing and its various applications. However, it is difficult to perfectly classify remotely sensed hyperspectral data by directly using classification ...
Fuding Xie, Dongcui Hu, Fangfei Li, Jun Yang, Deshan Liu   +4 more
doaj   +1 more source

Singular spectrum analysis for effective feature extraction in hyperspectral imaging

, 2014
As a very recent technique for time series analysis, Singular Spectrum Analysis (SSA) has been applied in many diverse areas, where an original 1D signal can be decomposed into a sum of components including varying trends, oscillations and noise ...
Zabalza, Jaime, Wang, Zheng, Ren, Jinchang, Marshall, Stephen, Wang, Jun   +4 more
core   +1 more source

Spectral Segmentation Multi-Scale Feature Extraction Residual Networks for Hyperspectral Image Classification

Remote Sensing, 2023
Hyperspectral image (HSI) classification is a vital task in hyperspectral image processing and applications. Convolutional neural networks (CNN) are becoming an effective approach for categorizing hyperspectral remote sensing images as deep learning ...
Jiamei Wang, Jiansi Ren, Yinbin Peng, Meilin Shi   +3 more
doaj   +1 more source

Effective feature extraction and data reduction with hyperspectral imaging in remote sensing

, 2014
Although PCA has been widely used for feature extraction and data reduction, it suffers from three main drawbacks: high computational cost, large memory requirement and low efficacy in processing large datasets such as HSI.
Zabalza, Jaime, Ren, Jinchang, Marshall, Stephen, Zheng, Jiangbin   +3 more
core   +1 more source

An Attention-Based Lattice Network for Hyperspectral Image Classification

, 2022
Convolutional neural networks (CNNs) with 3-D convolutional kernels are widely used for hyperspectral image (HSI) classification, which bring notable benefits in capturing joint spectral and spatial features.
Zhou, Jun, Nikzad, Mohammad, Gao, Yongsheng   +2 more
core   +1 more source