Results 121 to 130 of about 57,267 (303)

Hyperspectral Image Classification Using Spectral-Spatial Dual Random Fields With Gaussian and Markov Processes

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
This article presents a novel hyperspectral image (HSI) classification approach that integrates the sparse inducing variational Gaussian process (SIVGP) with a spatially adaptive Markov random field (SAMRF), termed G-MDRF.
Yaqiu Zhang, Lizhi Liu, Xinnian Yang
doaj   +1 more source

Ferroelectric Quantum Dots for Retinomorphic In‐Sensor Computing

Advanced Materials, EarlyView.
This work has provided a protocol for fabricating retinomorphic phototransistors by integrating ferroelectric ligands with quantum dots. The resulting device combines ferroelectricity, optical responsiveness, and low‐power operation to enable adaptive signal amplification and high recognition accuracy under low‐light conditions, while supporting ...
Tingyu Long, Huanyu Zhou, Jaewan Ko, Hongwei Tan, Jaemin Lim, Yanfei Zhao, Daehan Kang, Eojin Yoon, Gyeong‐Tak Go, Somin Kim, Seung‐Woo Lee, Chan‐Yul Park, Hyojun Choi, Hyeran Kim, Hyung Joong Yun, Sung Hyuk Park, Kwan Sik Park, Jeong Woo Park, Mungeun Kim, Yong Soo Cho, Ho Won Jang, Wenqiang Yang, Min Hyuk Park, Wan Ki Bae, Sebastiaan van Dijken, Joona Bang, Tae‐Woo Lee   +26 more
wiley   +1 more source

rft1d: Smooth One-Dimensional Random Field Upcrossing Probabilities in Python

Journal of Statistical Software, 2016
Through topological expectations regarding smooth, thresholded n-dimensional Gaussian continua, random field theory (RFT) describes probabilities associated with both the field-wide maximum and threshold-surviving upcrossing geometry.
Todd C. Pataky
doaj   +1 more source

Image texture analysis based on Gaussian Markov Random Fields

, 2014
Texture analysis is one of the key techniques of image understanding and processing with widespread applications from low level image segmentation to high level object recognition.
Dharmagunawardhana, Chathurika
core  

Gaussian and non-Gaussian random fields associated with Markov processes

, 1984
To every Markov process with a symmetric transition density, there correspond two random fields over the state space: a Gaussian field (the free field) φ and the occupation field T which describes amount of time the particle spends at each state.
Dynkin, E.B
core   +1 more source

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

Gaussian random fields and monogenic images

Applied and Computational Harmonic Analysis
In this paper, we focus on lighthouse anisotropic fractional Brownian fields (AFBFs), whose self-similarity depends solely on the so-called Hurst parameter, while anisotropy is revealed through the opening angle of an oriented spectral cone. This fractional field generalizes fractional Brownian motion and models rough natural phenomena.
Biermé, Hermine, Carré, Philippe, Lacaux, Céline, Launay, Claire   +3 more
openaire   +2 more sources

On degeneracy and invariances of random fields paths with applications in Gaussian process modelling [PDF]

, 2016
We study pathwise invariances and degeneracies of random fields with motivating applications in Gaussian process modelling. The key idea is that a number of structural properties one may wish to impose a priori on functions boil down to degeneracy ...
Roustant, Olivier, Ginsbourger, David, Durrande, Nicolas   +2 more
core   +1 more source

Mixed‐Metal Promotion in a Manganese‐Molybdenum Oxynitride as Catalyst to Integrate C─C and C─N Coupling Reactions for the Direct Synthesis of Acetonitrile from Syngas and Ammonia

Advanced Materials, EarlyView.
Transition metal oxy/carbo‐nitrides show great promise as catalysts for sustainable processes. A Mn‐Mo mixed‐metal oxynitride attains remarkable performance for the direct synthesis of acetonitrile, an important commodity chemical, via sequential C─N and C─C coupling from syngas (C1) and ammonia (N1) feedstocks.
M. Elena Martínez‐Monje, Wilson Henao, Tania Rodenas, Patricia Concepción, Virginia Pérez Dieste, Alexander Missyul, Giovanni Agostini, Gonzalo Prieto   +7 more
wiley   +1 more source

Incorporating covariance estimation uncertainty in spatial sampling design for prediction with trans-Gaussian random fields

Frontiers in Environmental Science, 2015
Recently, Spock and Pilz [38], demonstratedthat the spatial sampling design problem forthe Bayesian linear kriging predictor can betransformed to an equivalent experimentaldesign problem for a linear regression modelwith stochastic regression ...
Gunter eSpöck, Juergen ePilz
doaj   +1 more source