Results 41 to 50 of about 15,264 (300)

Nonlinear unmixing of hyperspectral images: Models and algorithms [PDF]

, 2013
When considering the problem of unmixing hyperspectral images, most of the literature in the geoscience and image processing areas relies on the widely used linear mixing model (LMM).
McLaughlin, Stephen; id_orcid, Hero, Alfred O, Jean-yves Tourneret, Cédric Richard, Hero, Alfred O., Dobigeon, Nicolas, McLaughlin, Steve, Bermudez, José Carlos M., Alfred O. Hero, Stephen Mclaughlin, Bermudez, José Carlos Moreira, Nicolas Dobigeon, Richard, Cédric, Tourneret, Jean-Yves, José Carlos M. Bermudez, Bermudez, José Carlos M   +14 more
core   +1 more source

Capsule Networks for Hyperspectral Image Classification [PDF]

IEEE Transactions on Geoscience and Remote Sensing, 2019
Convolutional neural networks (CNNs) have recently exhibited an excellent performance in hyperspectral image classification tasks. However, the straightforward CNN-based network architecture still finds obstacles when effectively exploiting the relationships between hyperspectral imaging (HSI) features in the spectral-spatial domain, which is a key ...
Mercedes Eugenia Paoletti, Juan Mario Haut, Rubén Fernández-Beltran, Javier Plaza, Antonio Plaza, Jun Li 0009, Filiberto Pla   +6 more
openaire   +2 more sources

New approaches on dimensionality reduction in hyperspectral images for classification purposes

, 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

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

Nonlinear spectral unmixing of hyperspectral images using Gaussian processes [PDF]

, 2012
This paper presents an unsupervised algorithm for nonlinear unmixing of hyperspectral images. The proposed model assumes that the pixel reflectances result from a nonlinear function of the abundance vectors associated with the pure spectral components ...
Altmann, Yoann, Altmann, Yoann; id_orcid, McLaughlin, Steve; id_orcid, Dobigeon, Nicolas, Tourneret, Jean-Yves, McLaughlin, Steve   +5 more
core   +1 more source

SYNERGETICS FRAMEWORK FOR HYPERSPECTRAL IMAGE CLASSIFICATION [PDF]

The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2013
Abstract. In this paper a new classification technique for hyperspectral data based on synergetics theory is presented. Synergetics – originally introduced by the physicist H. Haken – is an interdisciplinary theory to find general rules for pattern formation through selforganization and has been successfully applied in fields ranging from biology to ...
Müller, Rupert, Cerra, Daniele, Reinartz, Peter   +2 more
openaire   +4 more sources

Artificial Intelligence‐Assisted Workflow for Transmission Electron Microscopy: From Data Analysis Automation to Materials Knowledge Unveiling

Advanced Materials, EarlyView.
AI‐Assisted Workflow for (Scanning) Transmission Electron Microscopy: From Data Analysis Automation to Materials Knowledge Unveiling. Abstract (Scanning) transmission electron microscopy ((S)TEM) has significantly advanced materials science but faces challenges in correlating precise atomic structure information with the functional properties of ...
Marc Botifoll, Ivan Pinto‐Huguet, Enzo Rotunno, Thomas Galvani, Catalina Coll, Payam Habibzadeh Kavkani, Maria Chiara Spadaro, Yann‐Michel Niquet, Martin Børstad Eriksen, Sara Martí‐Sánchez, Georgios Katsaros, Giordano Scappucci, Peter Krogstrup, Giovanni Isella, Andreu Cabot, Gonzalo Merino, Pablo Ordejón, Stephan Roche, Vincenzo Grillo, Jordi Arbiol   +19 more
wiley   +1 more source

Tensor partial least squares for hyperspectral image classification

, 2022
A hyperspectral image is classically a three-way (or tensor) block of data. In order to extract information from it, it has to be classified using image classifiers.
Christopher E. Ndehedehe, Olayinka, Dupe Nihinlola, Dupe Nihinlola Olayinka, Okwuashi, Onuwa, Onuwa Okwuashi, Ndehedehe, Christopher E   +5 more
core   +1 more source

Interface‐Engineered Binary Framework Composites: Advancing Porous Materials for Precision Medicine

Advanced Materials Interfaces, EarlyView.
Binary framework composites integrate two complementary porous architectures into a unified platform, enabling multifunctional design, enhanced structural tunability, and improved physicochemical performance. By combining high surface area, ordered porosity, interfacial synergy, and versatile functionalization, these hybrid materials offer new ...
Navid Rabiee, Mohammad Rabiee, Mohammad Akrami‐Hasan‐Kohal, Sidi A. Bencherif   +3 more
wiley   +1 more source

An Innovative Intelligent System with Integrated CNN and SVM: Considering Various Crops through Hyperspectral Image Data

ISPRS International Journal of Geo-Information, 2021
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.
Shiuan Wan, Mei-Ling Yeh, Hong-Lin Ma
doaj   +1 more source