Results 81 to 90 of about 270,656 (363)

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

Global Information and Structure Tensor Guided Collaborative Representation for Anomaly Detection

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Anomaly detection is susceptible to complex background and interference noise. Local anomaly detection and collaborative representation detection can effectively suppress background.
Meiping Song, Zhenyu Guo, Lan Li, Shihui Liu, Haimo Bao, Jiakang Li   +5 more
doaj   +1 more source

Rotation Equivariant Convolutional Neural Networks for Hyperspectral Image Classification

IEEE Access, 2020
Detection of surface material based on hyperspectral imaging (HSI) analysis is an important and challenging task in remote sensing. It is widely known that spectral-spatial data exploitation performs better than traditional spectral pixel-wise procedures.
Mercedes E. Paoletti, Juan M. Haut, Swalpa Kumar Roy, Eligius M. T. Hendrix   +3 more
doaj   +1 more source

Morphological Convolutional Neural Networks for Hyperspectral Image Classification

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021
Convolutional neural networks (CNNs) have become quite popular for solving many different tasks in remote sensing data processing. The convolution is a linear operation, which extracts features from the input data.
Swalpa Roy, Ranjan Mondal, Mercedes E. Paoletti, Juan M. Haut, Antonio Plaza   +4 more
doaj   +1 more source

Characterization of Complex Stacking of Semiconductors Through Near Field Imaging and Spectroscopy

Advanced Materials, EarlyView.
SNOM imaging and spectroscopy on a mechanically cleaved facet is used to characterize the different layers of complex epitaxial heterostructures composed of a type II superlattice and highly doped semiconductors. Both the geometrical parameters of the stack and the optical properties of the individual layers and of the interfaces are retrieved, as well
Laure Tailpied, Clément Gureghian, Fréderic Fossard, Jean‐Sébastien Mérot, Jean‐Baptiste Rodriguez, Fernando Gonzalez‐Posada Flores, Grégory Vincent, Thierry Taliercio, Baptiste Fix   +8 more
wiley   +1 more source

Helios: Hyperspectral Hindsight Ostracker

2023 13th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS), 2023
In this paper we present our video object tracking algorithm HELIOS (HyperspEctraL hIndsight OStracker) designed for snapshot mosaic hyperspectral cameras, as part of our submission to the Third Hyperspectral Object Tracking Challenge 2023. HELIOS is based on a high-performance RGB-based one-stream tracking framework for joint feature learning and ...
Muszyński, Rafał, Luong, Hiep
openaire   +2 more sources

Full Crystallographic Imaging of Hexagonal Boron Nitride Monolayers with Phonon‐Enhanced Sum‐Frequency Microscopy

Advanced Materials, EarlyView.
A nonlinear optical microscopy technique is introduced that enables rapid imaging of hexagonal boron nitride monolayers, which are usually optically invisible. The nonlinear mixing of mid‐infrared and visible laser pulses enables full crystallographic imaging through phase‐resolved sum‐frequency generation microscopy, where the resonant excitation of a
Niclas S. Mueller, Alexander P. Fellows, Ben John, Andrew E. Naclerio, Christian Carbogno, Katayoun Gharagozloo‐Hubmann, Damián Baláž, Ryan A. Kowalski, Hendrik H. Heenen, Christoph Scheurer, Karsten Reuter, Joshua D. Caldwell, Martin Wolf, Piran R. Kidambi, Martin Thämer, Alexander Paarmann   +15 more
wiley   +1 more source

Mapping Materials and Dyes on Historic Tapestries Using Hyperspectral Imaging

Heritage, 2023
Hyperspectral imaging has emerged as a promising analytical method of artwork due to its potential in combining non-invasive analytical capabilities and imaging allowing the survey of the entire (or of a large area of the) surface of an artwork, which is
Constantina Vlachou-Mogire, Jon Danskin, John R. Gilchrist, Kathryn Hallett   +3 more
doaj   +1 more source

Comparison of Hyperspectral Imaging and Microvascular Doppler for Perfusion Monitoring of Free Flaps in an In Vivo Rodent Model [PDF]

, 2022
Philipp Becker, Sebastian Blatt, Andreas Pabst, Diana Heimes, Bilal Al‐Nawas, Peer W. Kämmerer, Daniel G. E. Thiem   +6 more
openalex   +1 more source

Spectral-Spatial Classification of Hyperspectral Imagery with 3D Convolutional Neural Network

Remote Sensing, 2017
Recent research has shown that using spectral–spatial information can considerably improve the performance of hyperspectral image (HSI) classification. HSI data is typically presented in the format of 3D cubes. Thus, 3D spatial filtering naturally offers
Ying Li, Haokui Zhang, Qiang Shen
semanticscholar   +1 more source