Results 51 to 60 of about 6,322 (191)

A Few Photons Among Many: Unmixing Signal and Noise for Photon-Efficient Active Imaging [PDF]

, 2016
Conventional LIDAR systems require hundreds or thousands of photon detections to form accurate depth and reflectivity images. Recent photon-efficient computational imaging methods are remarkably effective with only 1.0 to 3.0 detected photons per pixel ...
Goyal, Vivek K, Rapp, Joshua
core   +1 more source

Deep Learning‐Assisted Coherent Raman Scattering Microscopy

Advanced Intelligent Discovery, EarlyView.
The analytical capabilities of coherent Raman scattering microscopy are augmented through deep learning integration. This synergistic paradigm improves fundamental performance via denoising, deconvolution, and hyperspectral unmixing. Concurrently, it enhances downstream image analysis including subcellular localization, virtual staining, and clinical ...
Jianlin Liu, Rujia Liu, Xinyan Zhang, Xun Chen, Shuhua Yue   +4 more
wiley   +1 more source

Spatial Structural Priors for Sparse Unmixing of Remotely Sensed Hyperspectral Images

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
As spectral libraries continue to expand, sparse unmixing has become essential for effectively interpreting mixed pixels in remotely sensed hyperspectral data.
Shaoquan Zhang, Jiajun Zheng, Yuyang Liu, Fan Li, Chengzhi Deng, Antonio Plaza, Lianhui Liang, Zhi He, Shengqian Wang   +8 more
doaj   +1 more source

An adaptive stereo basis method for convolutive blind audio source separation [PDF]

, 2008
NOTICE: this is the author’s version of a work that was accepted for publication in Neurocomputing. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may ...
Abdallah, Abdallah, Aharon, Amari, Amari, Araki, Bell, Cardoso, Cardoso, Cardoso, Davies, Douglas, Emmanuel Vincent, Hyvärinen, Ikeda, Ikram, Jafari, Jourjine, Knapp, Kurita, Lewicki, Makino, Maria G. Jafari, Mark D. Plumbley, Matsuda, Mike E. Davies, Mitianoudis, Mitianoudis, O’Grady, Parra, Samer A. Abdallah, Saruwatari, Sawada, Schmidt, Smaragdis, Torkkola, Vincent, Vincent, Viste, Yilmaz, Zhang   +40 more
core   +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

A Multi-Attention Autoencoder for Hyperspectral Unmixing Based on the Extended Linear Mixing Model

Remote Sensing, 2023
Hyperspectral unmixing, which decomposes mixed pixels into the endmembers and corresponding abundances, is an important image process for the further application of hyperspectral images (HSIs).
Lijuan Su, Jun Liu, Yan Yuan, Qiyue Chen
doaj   +1 more source

Distributed Unmixing of Hyperspectral Data With Sparsity Constraint

, 2017
Spectral unmixing (SU) is a data processing problem in hyperspectral remote sensing. The significant challenge in the SU problem is how to identify endmembers and their weights, accurately. For estimation of signature and fractional abundance matrices in
Khoshsokhan, Sara, Rajabi, Roozbeh, Zayyani, Hadi   +2 more
core   +2 more sources

Fast and Robust Recursive Algorithms for Separable Nonnegative Matrix Factorization [PDF]

, 2013
In this paper, we study the nonnegative matrix factorization problem under the separability assumption (that is, there exists a cone spanned by a small subset of the columns of the input nonnegative data matrix containing all columns), which is ...
Gillis, Nicolas, Vavasis, Stephen A.
core   +2 more sources

Superior Intracellular Detection of Cytokines, Transcription Factors, and Phosphoproteins by CyTOF Compared With Fluorescent Cytometry

Cytometry Part A, EarlyView.
ABSTRACT Unraveling biological complexity, such as immune subset distribution in infectious disease(s), autoimmunity, or tumor heterogeneity, requires technologies capable of single‐cell proteomic analysis such as flow cytometry. Surface phenotyping alone is often insufficient, as interrogating functional capacity is required to determine cellular ...
Michael J. Cohen, Erika L. Smith‐Mahoney, Madison Bailey, Ling Wang, Lauren J. Tracey, Laura Polanco, David King, Christina Loh, Amedeo J. Cappione III, Anna C. Belkina, Jennifer E. Snyder‐Cappione   +10 more
wiley   +1 more source

Subspace Structure Regularized Nonnegative Matrix Factorization for Hyperspectral Unmixing

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2020
Hyperspectral unmixing is a crucial task for hyperspectral images (HSIs) processing, which estimates the proportions of constituent materials of a mixed pixel. Usually, the mixed pixels can be approximated using a linear mixing model. Since each material
Lei Zhou, Xueni Zhang, Jianbo Wang, Xiao Bai, Lei Tong, Liang Zhang, Jun Zhou, Edwin Hancock   +7 more
doaj   +1 more source