Results 51 to 60 of about 2,627,069 (171)

Predicting Classification Performance for Benchmark Hyperspectral Datasets

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2022
The classification of hyperspectral images (HSIs) is an essential application of remote sensing and it is addressed by numerous publications every year.
Bin Zhao, Haukur Isfeld Ragnarsson, Magnus O. Ulfarsson, Gabriele Cavallaro, Jon Atli Benediktsson   +4 more
doaj   +1 more source

AI‐Powered GPR Characterization of Peatland Underground Cavity Induced by Smoldering Wildfire: A Laboratory Proof‐of‐Concept

Safety Science and Technology, EarlyView.
We present an AI‐assisted ground‐penetrating radar framework to noninvasively detect and quantify smoldering wildfire‐induced subsurface cavities in peatlands. A ResNet model accurately predicts cavity geometry from GPR images, enabling improved assessment of underground fire damage and hazards.
Zifan Zhang, Zilong Wang, Yichao Zhang, Yanghan Su, Shaorun Lin, Xinyan Huang   +5 more
wiley   +1 more source

Hyperspectral Remote Sensing Image Synthesis via Superpixel and Energy-Guided Sampling-Based Diffusion Model

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Hyperspectral remote sensing images (HSIs) contain rich spectral information and have been widely used in agricultural monitoring, mineral analysis, and water monitoring.
Shaokai Weng, Hao Wu, Guowu Yuan, Shuanglin Zu   +3 more
doaj   +1 more source

An Efficient Representation-Based Subspace Clustering Framework for Polarized Hyperspectral Images

Remote Sensing, 2019
Recently, representation-based subspace clustering algorithms for hyperspectral images (HSIs) have been developed with the assumption that pixels belonging to the same land-cover class lie in the same subspace. Polarization is regarded to be a complement
Zhengyi Chen, Chunmin Zhang, Tingkui Mu, Tingyu Yan, Zeyu Chen, Yanqiang Wang   +5 more
doaj   +1 more source

HYPERSPECTRAL IMAGE KERNEL SPARSE SUBSPACE CLUSTERING WITH SPATIAL MAX POOLING OPERATION [PDF]

The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2016
In this paper, we present a kernel sparse subspace clustering with spatial max pooling operation (KSSC-SMP) algorithm for hyperspectral remote sensing imagery.
H. Zhang, H. Zhang, H. Zhai, W. Liao, L. Cao, L. Zhang, A. Pižurica   +6 more
doaj   +1 more source

AI‐Powered TAT‐Net Hyperspectral Imaging for Rapid and Accurate Differentiation of Sinonasal Inverted Papilloma and Malignancy

World Journal of Otorhinolaryngology - Head and Neck Surgery, EarlyView.
ABSTRACT Background Sinonasal inverted papilloma (IP) and malignancies share overlapping clinical and endoscopic features, and conventional histopathology frequently requires time‐consuming adjunct immunohistochemistry. Hyperspectral imaging (HSI) can capture subtle spectral changes associated with malignant transformation that are not apparent on ...
Hao‐Miao Zhao, Jia‐Chang Kong, Yun‐Ze Li, Wei Li, Xin Feng   +4 more
wiley   +1 more source

Development of a new spectral library classifier for airborne hyperspectral images on heterogeneous environments [PDF]

, 2011
The classification of hyperspectral images on heterogeneous environments without prior knowledge about the study area is a challenging task. Finding potential pure spectral signatures or endmembers (EM) of the various surface materials within an image is
Mende, Andre, Heiden, Uta, Buchroithner, Manfred, Hoja, Danielle, Bachmann, Martin   +4 more
core  

Hyperspectral Image Resolution Enhancement Based on Spectral Unmixing and Information Fusion [PDF]

, 2011
Hyperspectral imaging sensors exibit high spectral resolution, but normally low spatial resolution. This leads to spectral signatures of pixels originating from different object types. Such pixels are called mixed pixels.
Avbelj, Janja, Reinartz, Peter, Müller, Rupert, Cerra, Daniele, Bieniarz, Jakub   +4 more
core  

Sketch-Based Subspace Clustering of Hyperspectral Images

Remote Sensing, 2020
Sparse subspace clustering (SSC) techniques provide the state-of-the-art in clustering of hyperspectral images (HSIs). However, their computational complexity hinders their applicability to large-scale HSIs.
Shaoguang Huang, Hongyan Zhang, Qian Du, Aleksandra Pižurica   +3 more
doaj   +1 more source

Combining Multi-Dimensional Convolutional Neural Network (CNN) With Visualization Method for Detection of Aphis gossypii Glover Infection in Cotton Leaves Using Hyperspectral Imaging

Frontiers in Plant Science, 2021
Cotton is a significant economic crop. It is vulnerable to aphids (Aphis gossypii Glovers) during the growth period. Rapid and early detection has become an important means to deal with aphids in cotton. In this study, the visible/near-infrared (Vis/NIR)
Tianying Yan, Tianying Yan, Wei Xu, Wei Xu, Jiao Lin, Long Duan, Long Duan, Pan Gao, Pan Gao, Chu Zhang, Chu Zhang, Chu Zhang, Xin Lv, Xin Lv   +13 more
doaj   +1 more source