Results 41 to 50 of about 12,889,375 (285)

Hyperspectral Image Classification With Attention-Aided CNNs [PDF]

IEEE Transactions on Geoscience and Remote Sensing, 2021
Convolutional neural networks (CNNs) have been widely used for hyperspectral image classification. As a common process, small cubes are firstly cropped from the hyperspectral image and then fed into CNNs to extract spectral and spatial features.
Renlong Hang, Zhu Li 0001, Qingshan Liu 0001, Pedram Ghamisi, Shuvra S. Bhattacharyya   +4 more
openaire   +3 more sources

New approaches on dimensionality reduction in hyperspectral images for classification purposes [PDF]

, 2012
This paper presents a quasi-unsupervised methodology to detect endmembers within an hyperspectral scene and to derive a pixel-wise classification on its basis.
Rupert Mueller, Reinartz, Peter, Daniele Cerra, Müller, Rupert, Jakub Bieniarz, Cerra, Daniele, Peter Reinartz, Bieniarz, Jakub   +7 more
core   +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

Advances in hyperspectral image classification

IEEE SIGNAL PROCESSING MAGAZINE, 2014
The technological evolution of optical sensors over the last few decades has provided remote sensing analysts with rich spatial, spectral, and temporal information. In particular, the increase in spectral resolution of hyperspectral images (HSIs) and infrared sounders opens the doors to new application domains and poses new methodological challenges in
Camps-Valls, Gustavo, Tuia, Devis, Bruzzone, Lorenzo, Benediktsson, Jon Atli   +3 more
openaire   +1 more source

Wavelet based segmentation of hyperspectral colon tissue imagery [PDF]

, 2003
Segmentation is an early stage for the automated classification of tissue cells between normal and malignant types. We present an algorithm for unsupervised segmentation of images of hyperspectral human colon tissue cells into their constituent parts by ...
Rajpoot, Nasir M. (Nasir Mahmood), Rajpoot, Kashif   +1 more
core   +1 more source

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

Early Retinal UCHL1 Dysregulation Coupled With Synaptic Loss Reflects Alzheimer's Disease Severity

Advanced Science, EarlyView.
This study identifies synapse‐enriched deubiquitinase UCHL1 as an early Aβ‐responsive regulator of retinal synaptopathy in Alzheimer's disease. Retinal UCHL1 loss accompanies excitatory synapse degeneration, p75NTR activation, and neuroinflammation, and predicts Braak stage and cognitive decline. Aβ42 fibrils trigger synaptic and UCHL1 depletion before
Altan Rentsendorj, Jean‐Philippe Vit, Alexandre Hutton, Yosef Koronyo, Saba Shahin, Edward Robinson, Ernesto Barron, Anthony Rodriguez, Ousman Jallow, Julia Sheyn, Bhakta Prasad Gaire, Lalita Subedi, Miyah R. Davis, Barathan Gnanabharathi, Alexander V. Ljubimov, Stuart L. Graham, Vivek K. Gupta, Mehdi Mirzaei, Debra Hawes, Katlin Silm, Keith L. Black, Lon S. Schneider, Alfredo A. Sadun, Jesse G. Meyer, Dieu‐Trang Fuchs, Maya Koronyo‐Hamaoui   +25 more
wiley   +1 more source

EVALUATING THE INITIALIZATION METHODS OF WAVELET NETWORKS FOR HYPERSPECTRAL IMAGE CLASSIFICATION [PDF]

The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2016
The idea of using artificial neural network has been proven useful for hyperspectral image classification. However, the high dimensionality of hyperspectral images usually leads to the failure of constructing an effective neural network classifier.
P.-H. Hsu
doaj   +1 more source

Identification of an Osteochondral Erosion Process in Gout Driven by Fibrinogen‐Integrin Activation and Local MSU Crystallization

Advanced Science, EarlyView.
Cartilage injury promotes local fibrinogen deposition, which accelerates monosodium urate crystallization and activates integrin‐mediated matrix‐degradation. This self‐amplifying cycle drives gout‐related cartilage erosion. Disrupting fibrinogen deposition or restoring the cartilage barrier could interrupt this vicious cycle.
Hanlin Xu, Simin Bi, Zhechen Liu, Xiaofeng Zhou, Hengwei Qin, Nicola Dalbeth, Minbiao Ji, Yinghui Hua   +7 more
wiley   +1 more source

Segmentation-Aware Hyperspectral Image Classification

CoRR, 2019
To appear at International Geoscience and Remote Sensing Symposium (IGARSS ...
Berkan Demirel, Omer Ozdil, Yunus Emre Esin, Safak Ozturk   +3 more
openaire   +2 more sources