Results 41 to 50 of about 49,483 (287)

Hyperspectral Image Classification Based on Fusion of Curvature Filter and Domain Transform Recursive Filter

Remote Sensing, 2019
In recent decades, in order to enhance the performance of hyperspectral image classification, the spatial information of hyperspectral image obtained by various methods has become a research hotspot. For this work, it proposes a new classification method
Jianshang Liao, Liguo Wang
doaj   +1 more source

A DIVERSIFIED DEEP BELIEF NETWORK FOR HYPERSPECTRAL IMAGE CLASSIFICATION [PDF]

The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2016
In recent years, researches in remote sensing demonstrated that deep architectures with multiple layers can potentially extract abstract and invariant features for better hyperspectral image classification. Since the usual real-world hyperspectral image
P. Zhong, Z. Q. Gong, C. Schönlieb
doaj   +1 more source

Robust hyperspectral image classification with rejection fields

, 2015
In this paper we present a novel method for robust hyperspectral image classification using context and rejection. Hyperspectral image classification is generally an ill-posed image problem where pixels may belong to unknown classes, and obtaining ...
Bioucas-Dias, Jose, Condessa, Filipe, Kovacevic, Jelena   +2 more
core   +1 more source

Adaptive Markov random fields for joint unmixing and segmentation of hyperspectral image [PDF]

, 2013
Linear spectral unmixing is a challenging problem in hyperspectral imaging that consists of decomposing an observed pixel into a linear combination of pure spectra (or endmembers) with their corresponding proportions (or abundances). Endmember extraction
Benediktsson, Jon Atli, Dobigeon, Nicolas, Eches, Olivier, Tourneret, Jean-Yves   +3 more
core   +4 more sources

Hyperspectral Image Classification [PDF]

, 2012
One objective of hyperspectral data processing is to classify collected imagery into distinct material constituents relevant to particular applications, and produce classification maps that indicate where the constituents are present. Such information products can include land-cover maps for environmental remote sensing, surface mineral maps for ...
openaire   +1 more source

Optimized kernel minimum noise fraction transformation for hyperspectral image classification [PDF]

, 2017
This paper presents an optimized kernel minimum noise fraction transformation (OKMNF) for feature extraction of hyperspectral imagery. The proposed approach is based on the kernel minimum noise fraction (KMNF) transformation, which is a nonlinear ...
Gao, Lianru, Jia, Xiuping, Liao, Wenzhi, Zhang, Bing, Zhao, Bin   +4 more
core   +2 more sources

Hyperspectral Image Classification Based on Multi-Scale Residual Network with Attention Mechanism

Remote Sensing, 2021
In recent years, image classification on hyperspectral imagery utilizing deep learning algorithms has attained good results. Thus, spurred by that finding and to further improve the deep learning classification accuracy, we propose a multi-scale residual
Yuhao Qing, Wenyi Liu
doaj   +1 more source

Spectrally Tunable 2D Material‐Based Infrared Photodetectors for Intelligent Optoelectronics

Advanced Functional Materials, EarlyView.
Intelligent optoelectronics through spectral engineering of 2D material‐based infrared photodetectors. Abstract The evolution of intelligent optoelectronic systems is driven by artificial intelligence (AI). However, their practical realization hinges on the ability to dynamically capture and process optical signals across a broad infrared (IR) spectrum.
Junheon Ha, Yingshan Ma, Yong Nam An, Sung‐Un An, Hyeon Hak Jung, Suvi‐Tuuli Varjamo, Jiwon Yoo, Junho Min, Hanvit Kim, Faisal Ahmed, Sang Hoon Chae, Young Min Song, Weiwei Cai, Tawfique Hasan, Zhipei Sun, Dong‐Ho Kang, Hyeon‐Jin Shin, Yunyun Dai, Hoon Hahn Yoon   +18 more
wiley   +1 more source

A new bandwidth selection criterion for using SVDD to analyze hyperspectral data

, 2019
This paper presents a method for hyperspectral image classification that uses support vector data description (SVDD) with the Gaussian kernel function. SVDD has been a popular machine learning technique for single-class classification, but selecting the ...
Baumgardner, Chaudhuri, Evangelista, Kakde, Kakde, Peredriy, Walter   +6 more
core   +1 more source

Programmable In‐Situ Interactions Between Resins and Photopolymerized Structures for Seamlessly Integrated Optical Manufacturing of Microlenses

Advanced Functional Materials, EarlyView.
This study presents a dynamic interaction between liquid resins and photopolymerized structures enabled by an in situ light‐writing setup. By controlling a three‐phase interface through localized photopolymerization, which provides physical confinement for the remaining uncured resin regions, the approach establishes a programmable pathway that ...
Kibeom Kim, Sangmin Oh, Kahyun Hur, Hyesung Cho   +3 more
wiley   +1 more source