Results 41 to 50 of about 1,727,336 (191)

Micromachined Double‐Membrane Mechanically Tunable Metamaterial for Thermal Infrared Filtering

Advanced Photonics Research, Volume 6, Issue 5, May 2025.
Herein, a mechanically tunable double‐layer plasmonic metamaterial leveraging the extraordinary optical transmission effect observed in subwavelength arrays of openings within thin metal layers is presented. The concept is experimentally validated by integrating the proposed metamaterial structure into an electrostatic parallel‐plate actuator to create
Oleg Bannik, Fedor Kovalev, Mingkai Liu, Michal Zawierta, Dilusha Silva, Lorenzo Faraone, Mariusz Martyniuk, Ilya Shadrivov   +7 more
wiley   +1 more source

Passive Color Imaging Through Macroscopic Strong Scattering Media

Advanced Science, EarlyView.
Light reflected from distant targets is severely attenuated and scattered by dense fog. A color‐channel‐simulated, independently exposed sCMOS array (CISA), combined with a passive colorful de‐scattering pipeline (PCDP), captures and reconstructs extremely weak target signals.
Renrui Wang, Xiaoyu Wang, Jianyu Wang, Zhiyu Yang, Xiangyang Ji   +4 more
wiley   +1 more source

WU-Net: A Weakly-Supervised Unmixing Network for Remotely Sensed Hyperspectral Imagery [PDF]

IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium, 2019
Recently, enormous efforts have been made to improve the performance of the linear or nonlinear mixing model for hyperspectral unmixing, yet their ability to handle spectral variability and extract physically meaningful endmembers remains limited. Based on the powerful learning ability of deep learning, we propose a weakly-supervised unmixing network ...
Hong, Danfeng, Chanussot, Jocelyn, Yokoya, Naoto, Heiden, Uta, Heldens, Wieke, Zhu, Xiao Xiang   +5 more
openaire   +3 more sources

Flexible Integration of Structurally Diverse Spatial Multi‐Omics With AgaeSMO

Advanced Science, EarlyView.
AgaeSMO is a versatile and robust deep learning framework for flexible cross‐integration of spatial multi‐omics data. Leveraging a GATs network with a graph attention module, it learns joint embedding across diverse modalities, enabling integration of both structurally paired (e.g., spatial transcriptome‐epigenome, transcriptome‐proteome, transcriptome‐
Kunpeng Liu, Jinpo Su, Haotian Zhou, Yilin Shen, Mengke Qin, Yingjie Luo, Tiancai Wang, Zhenglin Chen, Yuanyuan Wang, Xiaokai Ma   +9 more
wiley   +1 more source

Snapshot Spatiotemporal‐Spectral Imaging Enabled by Joint Photonic Encoding

Advanced Science, EarlyView.
Spectra4D enables snapshot spatiotemporal‐spectral imaging by combining high‐speed DMD temporal modulation with CMOS‐integrated Fabry‐Pérot spectral encoding. From a single 2D measurement, a dual‐mask‐guided reconstruction network recovers multiple time‐resolved hyperspectral frames, enabling high‐fidelity observation of rapidly evolving spatial ...
Chunyu Chen, Junren Wen, Hao Sha, Chenying Yang, Ziyang Chen, Xiaochen Feng, Taiqin Chen, Wenzhen Zou, Xiangyu Chen, Xiangyang Ji, Guojun Liu, Yongbing Zhang   +11 more
wiley   +1 more source

Survey of Hyperspectral Earth Observation Applications from Space in the Sentinel-2 Context

Remote Sensing, 2018
In the last few decades, researchers have developed a plethora of hyperspectral Earth Observation (EO) remote sensing techniques, analysis and applications.
Julie Transon, Raphaël d’Andrimont, Alexandre Maugnard, Pierre Defourny   +3 more
doaj   +1 more source

Overcoming the Nyquist Limit in Molecular Hyperspectral Imaging by Reinforcement Learning

Advanced Intelligent Discovery, EarlyView.
Explorative spectral acquisition guide automatically selects informative spectral bands to optimize downstream tasks, outperforming full‐spectrum acquisition. The selected hyperspectral data are used for tasks such as unmixing and segmentation. BandOptiNet encodes selection states and outputs optimal bands to guide spectral acquisition. Recent advances
Xiaobin Tang, Yongqing Zhang, Xinyu Deng, Hyeon Jeong Lee, Delong Zhang   +4 more
wiley   +1 more source

Joint Bayesian Endmember Extraction and Linear Unmixing for Hyperspectral Imagery [PDF]

, 2009
This paper studies a fully Bayesian algorithm for endmember extraction and abundance estimation for hyperspectral imagery. Each pixel of the hyperspectral image is decomposed as a linear combination of pure endmember spectra following the linear mixing ...
Moussaoui, Saïd, N. Dobigeon, Coulon, Martial, Hero, Alfred O., A.O. Hero, Dobigeon, Nicolas, Tourneret, Jean-Yves, M. Coulon, Hero, Alfred, J.-Y. Tourneret, S. Moussaoui   +10 more
core   +1 more source

State of Science Assessment of Remote Sensing of Great Lakes Coastal Wetlands: Responding to an Operational Requirement

Remote Sensing, 2020
The purpose of this research was to develop a state of science synthesis of remote sensing technologies that could be used to track changes in Great Lakes coastal vegetation for the Great Lakes-St. Lawrence River Adaptive Management (GLAM) Committee. The
Lori White, Robert A. Ryerson, Jon Pasher, Jason Duffe   +3 more
doaj   +1 more source

Identifying Building Rooftops in Hyperspectral Imagery Using CNN With Pure Pixel Index

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021
Deep learning and traditional machine learning algorithms have been widely applied to enhance the classification accuracy in remote sensing images. However, due to the variety and changeability of buildings, identifying building rooftops based on remote ...
Yao Li, Chengming Ye, Yonggang Ge, Jose Marcato Junior, Wesley Nunes Goncalvese, Jonathan Li   +5 more
doaj   +1 more source