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2019 Index IEEE Transactions on Geoscience and Remote Sensing Vol. 57

2019 IEEE Transactions on Geoscience and Remote Sensing  
., Refo-cusing and Zoom-In Polar Format Algorithm for Curvilinear Spotlight SAR Imaging on Arbitrary Region of Interest; TGRS Oct. 2019 7995-8010 Hu, T., see Kang, Z., TGRS Jan. 2019 181-193 Hu, T.,  ...  ., +, TGRS Sept. 2019 6710-6725 Remote Sensing Image Reconstruction Using Tensor Ring Completion and Total Variation.  ...  ., +, TGRS Dec. 2019 9858-9877 Remote Sensing Image Reconstruction Using Tensor Ring Completion and Total Variation.  ... 
doi:10.1109/tgrs.2020.2967201 fatcat:kpfxoidv5bgcfo36zfsnxe4aj4

Can Terrestrial Restoration Methodologies be Transferred to Planetary Hyperspectral Imagery? A Quantitative Intercomparison and Discussion

Shuheng Zhao, Jie Li, Qiangqiang Yuan, Huanfeng Shen, Liangpei Zhang
2020 IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing  
 Abstract-Hyperspectral imaging is a significant remote sensing technology for deep space exploration to understand the planetary geological evolution.  ...  An improved nonreference quantitative evaluation method based on the High-resolution Imaging Science Experiment imagery is proposed.  ...  All the data can be obtained from the Mars Orbital Data Explorer produced by the PDS Geosciences Node at Washington University in St. Louis (https://ode.rsl.wustl. edu/mars/).  ... 
doi:10.1109/jstars.2020.3024911 fatcat:6gvm7afjt5g4jjxbh3dyf74y5q

Image Restoration for Remote Sensing: Overview and Toolbox [article]

Benhood Rasti, Yi Chang, Emanuele Dalsasso, Loïc Denis, Pedram Ghamisi
2021 arXiv   pre-print
in the remote sensing community.  ...  The quality of data acquired by remotely sensed imaging sensors (both active and passive) is often degraded by a variety of noise types and artifacts.  ...  Remote sensing data restoration attempts to recover an image from its corrupted version. The recovered image improves further analysis of the remote sensing images.  ... 
arXiv:2107.00557v2 fatcat:adn5fpdza5h4tbsycg7yw6rqzu

Proceedings of the second "international Traveling Workshop on Interactions between Sparse models and Technology" (iTWIST'14) [article]

L. Jacques, C. De Vleeschouwer, Y. Boursier, P. Sudhakar, C. De Mol, A. Pizurica, S. Anthoine, P. Vandergheynst, P. Frossard, C. Bilen, S. Kitic, N. Bertin, R. Gribonval, N. Boumal (+51 others)
2014 arXiv   pre-print
For its second edition, the iTWIST workshop took place in the medieval and picturesque town of Namur in Belgium, from Wednesday August 27th till Friday August 29th, 2014.  ...  talks, 10 oral presentations, and 14 posters on the following themes, all related to the theory, application and generalization of the "sparsity paradigm": Sparsity-driven data sensing and processing;  ...  There, the authors study 2 -stability for this class of decomposable norms with a general sufficiently smooth data fidelity.  ... 
arXiv:1410.0719v2 fatcat:4y3drgk3ujh5hopfn2p2runlzu

Joint segmentation and reconstruction of hyperspectral data with compressed measurements

Qiang Zhang, Robert Plemmons, David Kittle, David Brady, Sudhakar Prasad
2011 Applied Optics  
This work describes numerical methods for the joint reconstruction and segmentation of spectral images taken by compressive sensing coded aperture snapshot spectral imagers (CASSI).  ...  savings in acquisition time and data storage.  ...  Such high dimensional data pose challenges in both data acquisition and reconstruction.  ... 
doi:10.1364/ao.50.004417 pmid:21833118 fatcat:qutvqla3grel7f736dm4t5ooyi

2019 Index IEEE Transactions on Biomedical Engineering Vol. 66

2019 IEEE Transactions on Biomedical Engineering  
., +, TBME Jan. 2019 225-236 Multi-Source Ensemble Learning for the Remote Prediction of Parkinson's Disease in the Presence of Source-Wise Missing Data.  ...  ., +, TBME Jan. 2019 50-60 Scalable and Robust Tensor Decomposition of Spontaneous Stereotactic EEG Data.  ... 
doi:10.1109/tbme.2020.2964087 fatcat:mdfzsmdahnao5ccnuj232hycsm

2021 Index IEEE Transactions on Image Processing Vol. 30

2021 IEEE Transactions on Image Processing  
The Author Index contains the primary entry for each item, listed under the first author's name.  ...  -that appeared in this periodical during 2021, and items from previous years that were commented upon or corrected in 2021.  ...  ., +, TIP 2021 8540-8552 Dense Attention Fluid Network for Salient Object Detection in Optical Remote Sensing Images.  ... 
doi:10.1109/tip.2022.3142569 fatcat:z26yhwuecbgrnb2czhwjlf73qu

2020 Index IEEE Transactions on Circuits and Systems for Video Technology Vol. 30

2020 IEEE transactions on circuits and systems for video technology (Print)  
., +, TCSVT April 2020 970-982 Low CP Rank and Tucker Rank Tensor Completion for Estimating Missing Components in Image Data.  ...  ., +, TCSVT July 2020 1933-1945 Low CP Rank and Tucker Rank Tensor Completion for Estimating Missing Components in Image Data.  ...  A Memory-Efficient Hardware Architecture for Connected Component Labeling in Embedded System.  ... 
doi:10.1109/tcsvt.2020.3043861 fatcat:s6z4wzp45vfflphgfcxh6x7npu

A combined local and global motion estimation and compensation method for cardiac CT

Qiulin Tang, Beshan Chiang, Akinola Akinyemi, Alexander Zamyatin, Bibo Shi, Satoru Nakanishi, Bruce R. Whiting, Christoph Hoeschen
2014 Medical Imaging 2014: Physics of Medical Imaging  
variation minimization filter for low dose CT imaging Total Variation (TV) minimization is a well known technique in image processing for image denoising.  ...  Based on the compressive sensing (CS) theory, iterative based method with total variation (TV) minimization is proven to be a powerful framework for few-view tomographic image reconstruction.  ...  Studies have shown that there is variation in the agreement between operators viewing the same tissue [1] suggesting that a complimentary technique for verification could improve the robustness of the  ... 
doi:10.1117/12.2043492 fatcat:fyzpc5m6jbh7fjohqpdmtzkhte

Advances in Electron Microscopy with Deep Learning

Jeffrey Ede
2020 Zenodo  
and automatic data clustering by t-distributed stochastic neighbour embedding; adaptive learning rate clipping to stabilize learning; generative adversarial networks for compressed sensing with spiral  ...  Highlights include a comprehensive review of deep learning in electron microscopy; large new electron microscopy datasets for machine learning, dataset search engines based on variational autoencoders,  ...  In addition, part of the text in section 1.2 is adapted from our earlier work with permission 201 under a Creative Commons Attribution 4.0 73 license.  ... 
doi:10.5281/zenodo.4598227 fatcat:hm2ksetmsvf37adjjefmmbakvq

Advances in Electron Microscopy with Deep Learning

Jeffrey Ede
2020 Zenodo  
and automatic data clustering by t-distributed stochastic neighbour embedding; adaptive learning rate clipping to stabilize learning; generative adversarial networks for compressed sensing with spiral  ...  Highlights include a comprehensive review of deep learning in electron microscopy; large new electron microscopy datasets for machine learning, dataset search engines based on variational autoencoders,  ...  In addition, part of the text in section 1.2 is adapted from our earlier work with permission 201 under a Creative Commons Attribution 4.0 73 license.  ... 
doi:10.5281/zenodo.4591029 fatcat:zn2hvfyupvdwlnvsscdgswayci

MRK 1216 and NGC 1277 – an orbit-based dynamical analysis of compact, high-velocity dispersion galaxies

Akın Yıldırım, Remco C. E. van den Bosch, Glenn van de Ven, Bernd Husemann, Mariya Lyubenova, Jonelle L. Walsh, Karl Gebhardt, Kayhan Gültekin
2015 Monthly notices of the Royal Astronomical Society  
Combining deep HST imaging, wide-field IFU stellar kinematics, and complementary long-slit spectroscopic data out to 3 R_e, we construct orbit-based models to constrain their black hole masses, dark matter  ...  cent to the total mass budget within 1 R_e.  ...  The Marcario Low Resolution Spectrograph (LRS ) is named after Mike Marcario of High Lonesome Optics who fabricated several optics for the instrument but died before its completion.  ... 
doi:10.1093/mnras/stv1381 fatcat:4bcgfxhzxnfjtejp2hgaueary4

Advances in Electron Microscopy with Deep Learning

Jeffrey Ede
2020 Zenodo  
and automatic data clustering by t-distributed stochastic neighbour embedding; adaptive learning rate clipping to stabilize learning; generative adversarial networks for compressed sensing with spiral  ...  Highlights include a comprehensive review of deep learning in electron microscopy; large new electron microscopy datasets for machine learning, dataset search engines based on variational autoencoders,  ...  In addition, part of the text in section 1.2 is adapted from our earlier work with permission 201 under a Creative Commons Attribution 4.0 73 license.  ... 
doi:10.5281/zenodo.4399748 fatcat:63ggmnviczg6vlnqugbnrexsgy

Advances in Electron Microscopy with Deep Learning

Jeffrey Ede
2020 Zenodo  
and automatic data clustering by t-distributed stochastic neighbour embedding; adaptive learning rate clipping to stabilize learning; generative adversarial networks for compressed sensing with spiral  ...  Highlights include a comprehensive review of deep learning in electron microscopy; large new electron microscopy datasets for machine learning, dataset search engines based on variational autoencoders,  ...  In addition, part of the text in section 1.2 is adapted from our earlier work with permission 201 under a Creative Commons Attribution 4.0 73 license.  ... 
doi:10.5281/zenodo.4413249 fatcat:35qbhenysfhvza2roihx52afuy

Advances in Electron Microscopy with Deep Learning

Jeffrey Ede
2020 Zenodo  
and automatic data clustering by t-distributed stochastic neighbour embedding; adaptive learning rate clipping to stabilize learning; generative adversarial networks for compressed sensing with spiral  ...  Highlights include a comprehensive review of deep learning in electron microscopy; large new electron microscopy datasets for machine learning, dataset search engines based on variational autoencoders,  ...  In addition, part of the text in section 1.2 is adapted from our earlier work with permission 201 under a Creative Commons Attribution 4.0 73 license.  ... 
doi:10.5281/zenodo.4429792 fatcat:qs6yuapx4vdbdmwna7ix7nnwty
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