Results 51 to 60 of about 3,935,477 (223)

LEAD: Literature Enhanced Ab Initio Discovery of Nitride Dusting Layers for Enhanced Tunnel Magnetoresistance and Lower Resistance Magnetic Tunnel Junctions

Advanced Materials, EarlyView.
Magnetic tunnel junctions (MTJs) using MgO tunnel barriers face challenges of high resistance‐area product and low tunnel magnetoresistance (TMR). To discover alternative materials, Literature Enhanced Ab initio Discovery (LEAD) is developed. The LEAD‐predicted materials are theoretically evaluated, showing that MTJs with dusting of ScN or TiN on ...
Sabiq Islam, William S. Rogers, Chen‐Yu Hu, Ming‐Yuan Song, Xinyu Bao, Shehrin Sayed, Jean Anne C. Incorvia   +6 more
wiley   +1 more source

An Unsupervised Hyperspectral Band Selection Method Based on Shared Nearest Neighbor and Correlation Analysis

IEEE Access, 2019
Band selection is an important dimensionality reduction (DR) methodology for hyperspectral images (HSI). In recent years, many ranking-based clustering band selection methods have been developed.
Rongchao Yang, Jiangming Kan
doaj   +1 more source

Neuromorphic Electronics for Intelligence Everywhere: Emerging Devices, Flexible Platforms, and Scalable System Architectures

Advanced Materials, EarlyView.
The perspective presents an integrated view of neuromorphic technologies, from device physics to real‐time applicability, while highlighting the necessity of full‐stack co‐optimization. By outlining practical hardware‐level strategies to exploit device behavior and mitigate non‐idealities, it shows pathways for building efficient, scalable, and ...
Kapil Bhardwaj, Roshni Satheesh Babu, Yuxin Xia, Eva Bestelink, Radu Sporea, Nikos Hastas, Ioannis Zeimpekis, Dimitra G. Georgiadou, Sayani Majumdar   +8 more
wiley   +1 more source

Unsupervised Band Selection Using Fused HSI and LiDAR Attention Integrating With Autoencoder [PDF]

Band selection in hyperspectral imaging (HSI) is critical for optimising data processing and enhancing analytical accuracy. Traditional approaches have predominantly concentrated on analysing spectral and pixel characteristics within individual bands ...
Zhou, Jun, Tian, Hui, Wang, Jing, Yang, Judy X, Liew, Alan Wee Chung   +4 more
core   +1 more source

Highly-Constrained Unsupervised Hyperspectral Band Selection via Quality-aware Latent Feature Clustering

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Unsupervised band selection (UBS), which reduces dimensionality without relying on costly labeled data, is pivotal for hyperspectral image (HSI) analysis.
Ping Ma, Jinchang Ren, Rongjun Chen, Erlei Zhang, Genyun Sun, Yanling Han, Jing Wang   +6 more
doaj   +1 more source

Restoration and Calibration of Tilting Hyperspectral Super-Resolution Image

Sensors, 2020
Tilting sampling is a novel sampling mode for achieving a higher resolution of hyperspectral imagery. However, most studies on the tilting image have only focused on a single band, which loses the features of hyperspectral imagery.
Xizhen Zhang, Aiwu Zhang, Mengnan Li, Lulu Liu, Xiaoyan Kang   +4 more
doaj   +1 more source

Unsupervised hyperspectral band selection via multi-feature information-maximization clustering

, 2017
International audienceThis paper presents a new approach for unsupervised band selection in the context of hyperspectral imaging. The hyperspectral band selection (HBS) task is considered as a clustering problem: bands are clustered in the image space ...
Berthoumieu, Yannick, Marco Bevilacqua, Bevilacqua, Marco, Yannick Berthoumieu   +3 more
core   +1 more source

Organic Materials of Tomorrow: Horizons of Artificial Intelligence

Advanced Materials, EarlyView.
This review examines machine learning techniques accelerating the discovery of organic semiconductors by linking molecular structure to properties. Key methods include graph neural networks, generative models, and active learning. Applications to organic photovoltaics demonstrate practical impact.
Harold Mena, J. Terence Blaskovits, Kun‐Han Lin, Denis Andrienko   +3 more
wiley   +1 more source

University Concert Band, University Symphonic Band, February 17, 1980

, 2018
Recorded during a live performance at Miller Auditorium, Western Michigan University, Kalamazoo, Michigan, February 17, 1980, program no. 205 of the Department of Music's 1979-1980 season.University Concert Band, Gregory Talford, conductor (1st-4th works)
Western Michigan University. Concert Band
core   +1 more source

Modular, Textile‐Based Soft Robotic Grippers for Agricultural Produce Handling

Advanced Robotics Research, EarlyView.
This article introduces textile‐based pneumatic grippers that transform simple textiles into robust bending actuators. Detailed experiments uncover how cut geometry and fabric selection shape performance. Successful handling of fragile agricultural items showcases the potential of textile robotics for safe, scalable automation in food processing and ...
Zeyu Hou, Eran Beeri Bamani, Joao Buzzatto, Bryan Busby, Lucas Ferrari Gerez   +4 more
wiley   +1 more source