Results 81 to 90 of about 98,568 (293)

Potassium‐Impurity‐Modulated Self‐Trapped Excitons and Energy Transfer in Phase‐Separated, Mn4+‐Doped Li2HfF6

Advanced Science, EarlyView.
Li2HfF6 contains two spectroscopically distinct self‐trapped excitons (STEs): intrinsic STE1 and redshifted, K‐associated STE2. Potassium incorporation stabilizes STE2, which selectively sensitizes Mn4+ red emission. This work uncovers the often‐overlooked role of trace K impurities, demonstrating impurity modulation as an effective strategy for tuning
Menuka Adhikari, Thomas Murray, Cameron J. Lewis, Jett Wu, Hari Adhikari, Cheng Li, Jianguo Wen, Hui Wu, Zhiping Luo   +8 more
wiley   +1 more source

KDAD: Knowledge Distillation-Based Anomaly Detection for Thermal Infrared Hyperspectral Image

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Autoencoder (AE) is extensively utilized in hyperspectral anomaly detection (HAD) tasks owing to its robust feature extraction and image reconstruction capabilities. However, AE lacks constraints on anomaly samples during the training process, leading to
Enyu Zhao, Hao Zhang, Nianxin Qu, Yulei Wang, Yongguang Zhao   +4 more
doaj   +1 more source

Residual component analysis of hyperspectral images - Application to joint nonlinear unmixing and nonlinearity detection [PDF]

, 2014
This paper presents a nonlinear mixing model for joint hyperspectral image unmixing and nonlinearity detection. The proposed model assumes that the pixel reflectances are linear combinations of known pure spectral components corrupted by an additional ...
Altmann, Yoann, Altmann, Yoann; id_orcid, Tourneret, Jean-yves, Tourneret, Jean Yves, Yoann Altmann, Steve Mclaughlin, McLaughlin, Steve; id_orcid, Nicolas Dobigeon, Jean-yves Tourneret, Dobigeon, Nicolas, McLaughlin, Steve   +10 more
core   +1 more source

Real‐Time Multicolor Fluorescence Microscopy via Cross‐Channel Acquisition and Deep‐Learning‐Based Inference

Advanced Intelligent Discovery, EarlyView.
Sequential multicolor fluorescence imaging in dynamic microsystems is constrained by acquisition speed and excitation dose. This study introduces a real‐time framework to reconstruct spectrally separated channels from reduced cross‐channel acquisitions (frames containing mixed spectral contributions).
Juan J. Huaroto, Yuxin Jin, Nicholas Roy, Sarthak Misra   +3 more
wiley   +1 more source

Self- and Cross-Attention Enhanced Transformer for Visible and Thermal Infrared Hyperspectral Image Classification

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Visible hyperspectral image (V-HSI) and thermal infrared hyperspectral image (TI-HSI) have been crucial data sources for land cover classification. V-HSI can directly provide information of land surface, such as shape, color, texture, and other features.
Enyu Zhao, Yongfang Su, Nianxin Qu, Yulei Wang, Caixia Gao, Jian Zeng   +5 more
doaj   +1 more source

Editorial for Special Issue “Hyperspectral Imaging and Applications”

Remote Sensing, 2019
Due to advent of sensor technology, hyperspectral imaging has become an emerging technology in remote sensing. Many problems, which cannot be resolved by multispectral imaging, can now be solved by hyperspectral imaging.
Chein-I Chang, Meiping Song, Junping Zhang, Chao-Cheng Wu   +3 more
doaj   +1 more source

Hyperspectral Unmixing Hierarchies

CoRR
Unmixing reveals the spatial distribution and spectral details of different constituents, called endmembers, in a hyperspectral image. Because unmixing has limited ground truth requirements, can accommodate mixed pixels, and is closely tied to light propagation, it is a uniquely powerful tool for analyzing hyperspectral images.
Joseph L. Garrett, P. S. Vishnu, Pauliina Salmi, Daniela Lupu, Nitesh Kumar Singh, Ion Necoara, Tor Arne Johansen   +6 more
openaire   +2 more sources

Hyperspectral Data Augmentation

CoRR, 2019
Submitted to IEEE Geoscience and Remote Sensing ...
Jakub Nalepa, Michal Myller, Michal Kawulok   +2 more
openaire   +2 more sources

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

Spatially Informed Feature Selection and Machine Learning in Matrix‐Assisted Laser Desorption/Ionization Imaging for Cohort‐Scale Molecular Tissue Phenomics in Glioblastoma

Advanced Intelligent Discovery, EarlyView.
Matrix‐assisted laser desorption/ionization imaging‐based identification of reliable small molecule markers across heterogeneous glioblastoma cohorts is challenging with intensity‐only methods. We present spatially informed feature selection (SIFS), a spatially informed framework that prioritizes molecules consistently colocalizing with histopathology.
Shad A. Mohammed, Denis Abu Sammour, Dirk C. Hoffmann, Philipp Sievers, Tobias Bausbacher, Melissa Hahn, Yasemin Ucal, Iris Mildenberger, Christiane A. Opitz, Stefan Schmidt, Michael Platten, Oliver Wasenmüller, Wolfgang Wick, Andreas von Deimling, Tobias Kessler, Carsten Hopf   +15 more
wiley   +1 more source