skip to main content
Language:
Search Limited to: Search Limited to: Resource type Show Results with: Show Results with: Search type Index

Results 1 - 20 of 2,109,928  for All Library Resources

Sorted by: Sorted by: RelevanceOr hit Enter to replace sort method
Results 1 2 3 4 5 next page
Show only
Result Number Material Type Add to My Shelf Action Record Details and Options
1
Fast Single Image Super-Resolution Using a New Analytical Solution for l2–l2 Problems
Fast Single Image Super-Resolution Using a New Analytical Solution for l2–l2 Problems
Material Type:
Article 		Add to My Research

Fast Single Image Super-Resolution Using a New Analytical Solution for l2–l2 Problems

IEEE transactions on image processing, 2016-08, Vol.25 (n° 8) [Peer Reviewed Journal]

Distributed under a Creative Commons Attribution 4.0 International License ;ISSN: 1057-7149 ;EISSN: 1941-0042 ;DOI: 10.1109/TIP.2016.2567075

Digital Resources/Online E-Resources

Citations Cited by
2
Validation of synthesized normal‐resolution image data generated from high‐resolution acquisitions on a commercial CT scanner
Validation of synthesized normal‐resolution image data generated from high‐resolution acquisitions on a commercial CT scanner
Material Type:
Article 		Add to My Research

Validation of synthesized normal‐resolution image data generated from high‐resolution acquisitions on a commercial CT scanner

Medical physics (Lancaster), 2020-10, Vol.47 (10), p.4775-4785 [Peer Reviewed Journal]

2020 American Association of Physicists in Medicine ;2020 American Association of Physicists in Medicine. ;ISSN: 0094-2405 ;EISSN: 2473-4209 ;DOI: 10.1002/mp.14395 ;PMID: 32677085

Full text available

Citations Cited by
3
FRESH-FRI-Based Single-Image Super-Resolution Algorithm
FRESH-FRI-Based Single-Image Super-Resolution Algorithm
Material Type:
Article 		Add to My Research

FRESH-FRI-Based Single-Image Super-Resolution Algorithm

IEEE transactions on image processing, 2016-08, Vol.25 (8), p.3723-3735 [Peer Reviewed Journal]

ISSN: 1057-7149 ;EISSN: 1941-0042 ;DOI: 10.1109/TIP.2016.2563178 ;PMID: 27168595 ;CODEN: IIPRE4

Digital Resources/Online E-Resources

Citations Cited by
4
Medical image super‐resolution using correlation filter interleaved progressive convolution network (CFIPC)
Medical image super‐resolution using correlation filter interleaved progressive convolution network (CFIPC)
Material Type:
Article 		Add to My Research

Medical image super‐resolution using correlation filter interleaved progressive convolution network (CFIPC)

Electronics letters, 2022-04, Vol.58 (9), p.360-362 [Peer Reviewed Journal]

2022 The Authors. published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology ;ISSN: 0013-5194 ;EISSN: 1350-911X ;DOI: 10.1049/ell2.12467

Full text available

Citations Cited by
5
Enhancing Remote Sensing Image Super-Resolution Guided by Bicubic-Downsampled Low-Resolution Image
Enhancing Remote Sensing Image Super-Resolution Guided by Bicubic-Downsampled Low-Resolution Image
Material Type:
Article 		Add to My Research

Enhancing Remote Sensing Image Super-Resolution Guided by Bicubic-Downsampled Low-Resolution Image

Remote sensing (Basel, Switzerland), 2023-07, Vol.15 (13), p.3309 [Peer Reviewed Journal]

COPYRIGHT 2023 MDPI AG ;2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 2072-4292 ;EISSN: 2072-4292 ;DOI: 10.3390/rs15133309

Full text available

Citations Cited by
6
Super‐resolution with adversarial loss on the feature maps of the generated high‐resolution image
Super‐resolution with adversarial loss on the feature maps of the generated high‐resolution image
Material Type:
Article 		Add to My Research

Super‐resolution with adversarial loss on the feature maps of the generated high‐resolution image

Electronics letters, 2022-01, Vol.58 (2), p.47-49 [Peer Reviewed Journal]

2021 The Authors. published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology ;ISSN: 0013-5194 ;EISSN: 1350-911X ;DOI: 10.1049/ell2.12360

Full text available

Citations Cited by
7
Recycling diagnostic MRI for empowering brain morphometric research – Critical & practical assessment on learning-based image super-resolution
Recycling diagnostic MRI for empowering brain morphometric research – Critical & practical assessment on learning-based image super-resolution
Material Type:
Article 		Add to My Research

Recycling diagnostic MRI for empowering brain morphometric research – Critical & practical assessment on learning-based image super-resolution

NeuroImage (Orlando, Fla.), 2021-12, Vol.245, p.118687-118687, Article 118687 [Peer Reviewed Journal]

2021 The Author(s) ;Copyright © 2021 The Author(s). Published by Elsevier Inc. All rights reserved. ;2021. The Author(s) ;ISSN: 1053-8119 ;EISSN: 1095-9572 ;DOI: 10.1016/j.neuroimage.2021.118687 ;PMID: 34732323

Full text available

Citations Cited by
8
A novel strategy to develop deep learning for image super-resolution using original ultra-high-resolution computed tomography images of lung as training dataset
A novel strategy to develop deep learning for image super-resolution using original ultra-high-resolution computed tomography images of lung as training dataset
Material Type:
Article 		Add to My Research

A novel strategy to develop deep learning for image super-resolution using original ultra-high-resolution computed tomography images of lung as training dataset

Japanese journal of radiology, 2022-01, Vol.40 (1), p.38-47 [Peer Reviewed Journal]

Japan Radiological Society 2021 ;2021. Japan Radiological Society. ;Japan Radiological Society 2021. ;ISSN: 1867-1071 ;EISSN: 1867-108X ;DOI: 10.1007/s11604-021-01184-8 ;PMID: 34318444

Full text available

Citations Cited by
9
BAS ^Net: Boundary-Aware Semi-Supervised Semantic Segmentation Network for Very High Resolution Remote Sensing Images
BAS ^Net: Boundary-Aware Semi-Supervised Semantic Segmentation Network for Very High Resolution Remote Sensing Images
Material Type:
Article 		Add to My Research

BAS ^Net: Boundary-Aware Semi-Supervised Semantic Segmentation Network for Very High Resolution Remote Sensing Images

IEEE journal of selected topics in applied earth observations and remote sensing, 2020, Vol.13, p.5398-5413 [Peer Reviewed Journal]

Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2020 ;ISSN: 1939-1404 ;EISSN: 2151-1535 ;DOI: 10.1109/JSTARS.2020.3021098 ;CODEN: IJSTHZ

Full text available

Citations Cited by
10
'Democracy in microscopy': cheap light microscope delivers super-resolution images
'Democracy in microscopy': cheap light microscope delivers super-resolution images
Material Type:
Article 		Add to My Research

'Democracy in microscopy': cheap light microscope delivers super-resolution images

Nature (London), 2023-04, Vol.616 (7957), p.417-418 [Peer Reviewed Journal]

Copyright Nature Publishing Group Apr 20, 2023 ;ISSN: 0028-0836 ;EISSN: 1476-4687 ;DOI: 10.1038/d41586-023-01267-8 ;PMID: 37072519

Full text available

Citations Cited by
11
Optimized generation of high-resolution phantom images using cGAN: Application to quantification of Ki67 breast cancer images
Optimized generation of high-resolution phantom images using cGAN: Application to quantification of Ki67 breast cancer images
Material Type:
Article 		Add to My Research

Optimized generation of high-resolution phantom images using cGAN: Application to quantification of Ki67 breast cancer images

PloS one, 2018-05, Vol.13 (5), p.e0196846-e0196846 [Peer Reviewed Journal]

COPYRIGHT 2018 Public Library of Science ;COPYRIGHT 2018 Public Library of Science ;This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication: https://creativecommons.org/publicdomain/zero/1.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 1932-6203 ;EISSN: 1932-6203 ;DOI: 10.1371/journal.pone.0196846 ;PMID: 29742125

Full text available

Citations Cited by
12
CN-BSRIQA: Cascaded network - blind super-resolution image quality assessment
CN-BSRIQA: Cascaded network - blind super-resolution image quality assessment
Material Type:
Article 		Add to My Research

CN-BSRIQA: Cascaded network - blind super-resolution image quality assessment

Alexandria engineering journal, 2024-03, Vol.91, p.580-591 [Peer Reviewed Journal]

2024 The Author(s) ;ISSN: 1110-0168 ;DOI: 10.1016/j.aej.2024.02.007

Full text available

Citations Cited by
13
Correlation functions quantify super-resolution images and estimate apparent clustering due to over-counting
Correlation functions quantify super-resolution images and estimate apparent clustering due to over-counting
Material Type:
Article 		Add to My Research

Correlation functions quantify super-resolution images and estimate apparent clustering due to over-counting

PloS one, 2012-02, Vol.7 (2), p.e31457-e31457 [Peer Reviewed Journal]

COPYRIGHT 2012 Public Library of Science ;COPYRIGHT 2012 Public Library of Science ;2012 Veatch et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License: https://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;Veatch et al. 2012 ;ISSN: 1932-6203 ;EISSN: 1932-6203 ;DOI: 10.1371/journal.pone.0031457 ;PMID: 22384026

Full text available

Citations Cited by
14
Statistical segmentation model for accurate electrode positioning in Parkinson's deep brain stimulation based on clinical low-resolution image data and electrophysiology
Statistical segmentation model for accurate electrode positioning in Parkinson's deep brain stimulation based on clinical low-resolution image data and electrophysiology
Material Type:
Article 		Add to My Research

Statistical segmentation model for accurate electrode positioning in Parkinson's deep brain stimulation based on clinical low-resolution image data and electrophysiology

PloS one, 2024-03, Vol.19 (3), p.e0298320-e0298320 [Peer Reviewed Journal]

Copyright: © 2024 Varga et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. ;COPYRIGHT 2024 Public Library of Science ;2024 Varga et al 2024 Varga et al ;ISSN: 1932-6203 ;EISSN: 1932-6203 ;DOI: 10.1371/journal.pone.0298320 ;PMID: 38483943

Full text available

Citations Cited by
15
Correction: Statistical segmentation model for accurate electrode positioning in Parkinson's deep brain stimulation based on clinical low-resolution image data and electrophysiology
Correction: Statistical segmentation model for accurate electrode positioning in Parkinson's deep brain stimulation based on clinical low-resolution image data and electrophysiology
Material Type:
Article 		Add to My Research

Correction: Statistical segmentation model for accurate electrode positioning in Parkinson's deep brain stimulation based on clinical low-resolution image data and electrophysiology

PloS one, 2024-04, Vol.19 (4), p.e0302985-e0302985 [Peer Reviewed Journal]

Copyright: © 2024 Varga et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. ;COPYRIGHT 2024 Public Library of Science ;2024 Varga et al 2024 Varga et al ;ISSN: 1932-6203 ;EISSN: 1932-6203 ;DOI: 10.1371/journal.pone.0302985 ;PMID: 38683813

Full text available

Citations Cited by
16
Dual-source spiral CT with pitch up to 3.2 and 75 ms temporal resolution: Image reconstruction and assessment of image quality
Dual-source spiral CT with pitch up to 3.2 and 75 ms temporal resolution: Image reconstruction and assessment of image quality
Material Type:
Article 		Add to My Research

Dual-source spiral CT with pitch up to 3.2 and 75 ms temporal resolution: Image reconstruction and assessment of image quality

Medical physics (Lancaster), 2009-12, Vol.36 (12), p.5641-5653 [Peer Reviewed Journal]

American Association of Physicists in Medicine ;2009 American Association of Physicists in Medicine ;ISSN: 0094-2405 ;EISSN: 2473-4209 ;DOI: 10.1118/1.3259739 ;PMID: 20095277 ;CODEN: MPHYA6

Full text available

Citations Cited by
17
A high-resolution image time series of the Gorner Glacier – Swiss Alps – derived from repeated unmanned aerial vehicle surveys
A high-resolution image time series of the Gorner Glacier – Swiss Alps – derived from repeated unmanned aerial vehicle surveys
Material Type:
Article 		Add to My Research

A high-resolution image time series of the Gorner Glacier – Swiss Alps – derived from repeated unmanned aerial vehicle surveys

Earth system science data, 2019-04, Vol.11 (2), p.579-588 [Peer Reviewed Journal]

COPYRIGHT 2019 Copernicus GmbH ;2019. This work is published under https://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 1866-3516 ;ISSN: 1866-3508 ;EISSN: 1866-3516 ;DOI: 10.5194/essd-11-579-2019

Full text available

Citations Cited by
18
DRL-GAN: Dual-Stream Representation Learning GAN for Low-Resolution Image Classification in UAV Applications
DRL-GAN: Dual-Stream Representation Learning GAN for Low-Resolution Image Classification in UAV Applications
Material Type:
Article 		Add to My Research

DRL-GAN: Dual-Stream Representation Learning GAN for Low-Resolution Image Classification in UAV Applications

IEEE journal of selected topics in applied earth observations and remote sensing, 2021, Vol.14, p.1705-1716 [Peer Reviewed Journal]

Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2021 ;ISSN: 1939-1404 ;EISSN: 2151-1535 ;DOI: 10.1109/JSTARS.2020.3043109 ;CODEN: IJSTHZ

Full text available

Citations Cited by
19
Arcsecond resolution images of the chemical structure of the low-mass protostar IRAS 16293-2422 An overview of a large molecular line survey from the Submillimeter Array
Arcsecond resolution images of the chemical structure of the low-mass protostar IRAS 16293-2422 An overview of a large molecular line survey from the Submillimeter Array
Material Type:
Article 		Add to My Research

Arcsecond resolution images of the chemical structure of the low-mass protostar IRAS 16293-2422 An overview of a large molecular line survey from the Submillimeter Array

Astronomy and astrophysics (Berlin), 2011-10, Vol.534, p.A100 [Peer Reviewed Journal]

2015 INIST-CNRS ;ISSN: 0004-6361 ;EISSN: 1432-0746 ;DOI: 10.1051/0004-6361/201117139 ;CODEN: AAEJAF

Full text available

Citations Cited by
20
Implications of a High Angular Resolution Image of the Sunyaev-Zel'Dovich Effect in RXJ1347–1145
Implications of a High Angular Resolution Image of the Sunyaev-Zel'Dovich Effect in RXJ1347–1145
Material Type:
Article 		Add to My Research

Implications of a High Angular Resolution Image of the Sunyaev-Zel'Dovich Effect in RXJ1347–1145

The Astrophysical journal, 2010-06, Vol.716 (1), p.739-745 [Peer Reviewed Journal]

ISSN: 0004-637X ;EISSN: 1538-4357 ;DOI: 10.1088/0004-637X/716/1/739

Full text available

Citations Cited by

Results 1 - 20 of 2,109,928  for All Library Resources

Sorted by: Sorted by: RelevanceOr hit Enter to replace sort method
Results 1 2 3 4 5 next page

Personalize your results

  1. Edit

Refine Search Results

Expand My Results

  1.   

Show only

  1. Peer-reviewed Journals (1,546,626)

Refine My Results

Creation Date 

From To
Refine
  1. Before 1957  (17,984)
  2. 1957 To 1973  (12,064)
  3. 1974 To 1990  (39,044)
  4. 1991 To 2008  (457,932)
  5. After 2008  (1,580,320)
  6. More options open sub menu

Resource Type 

  1. Articles  (1,667,529)
  2. Patents  (202,646)
  3. magazinearticle  (79,907)
  4. Book Chapters  (55,214)
  5. Images  (25,598)
  6. Reviews  (18,127)
  7. Conference Proceedings  (12,962)
  8. Thesises (postgraduate)  (11,711)
  9. Reports  (8,921)
  10. Newspaper Articles  (8,343)
  11. Datasets  (6,360)
  12. References  (3,873)
  13. Books  (3,654)
  14. Newsletter Articles  (1,788)
  15. Web Resources  (1,393)
  16. Drawing/Maps  (870)
  17. Text Resources  (546)
  18. Standards  (170)
  19. Other  (162)
  20. Videos  (63)
  21. More options open sub menu

Subject 

  1. Science & Technology  (1,234,754)
  2. Life Sciences & Biomedicine  (590,286)
  3. Physical Sciences  (450,695)
  4. Technology  (355,346)
  5. Humans  (304,084)
  6. Physics  (300,511)
  7. Science & Technology - Other Topics  (207,237)
  8. Male  (156,667)
  9. Engineering  (154,710)
  10. Animals  (151,154)
  11. Female  (150,367)
  12. Multidisciplinary Sciences  (145,446)
  13. Chemistry  (143,083)
  14. Materials Science  (142,660)
  15. Algorithms  (110,633)
  16. Materials Science, Multidisciplinary  (110,045)
  17. Physics, Applied  (99,108)
  18. Neurosciences & Neurology  (87,801)
  19. Adult  (86,199)
  20. Environmental Sciences & Ecology  (83,442)
  21. More options open sub menu

Language 

  1. English  (2,068,828)
  2. Japanese  (222,947)
  3. French  (40,735)
  4. Chinese  (40,487)
  5. German  (20,950)
  6. Korean  (9,298)
  7. Portuguese  (5,891)
  8. Spanish  (4,943)
  9. Russian  (2,049)
  10. Norwegian  (1,936)
  11. Italian  (771)
  12. Turkish  (548)
  13. Polish  (539)
  14. Swedish  (337)
  15. Afrikaans  (313)
  16. Dutch  (309)
  17. Croatian  (301)
  18. Czech  (277)
  19. Hebrew  (200)
  20. More options open sub menu

Journal Title 

  1. Applied Sciences  (12,914)
  2. Arxiv.Org  (17,239)
  3. Journal Of Physics. Conference Series  (12,456)
  4. Nature Communications  (24,666)
  5. Neuroimage  (13,949)
  6. Plos One  (38,457)
  7. Remote Sensing  (23,872)
  8. Scientific Reports  (59,442)
  9. Sensors  (19,818)
  10. The Astrophysical Journal  (24,528)
  11. More options open sub menu
INSPIRE LIBRARY - TON DUC THANG UNIVERSITY (84-028) 37 755 057 Feedback
19 Nguyen Huu Tho St. Dist.7, HCM thuvien@tdtu.edu.vn

Copyright © 2017 INSPIRE LIBRARY - TON DUC THANG UNIVERSITY

Searching Remote Databases, Please Wait