Pith. sign in

Paper Citation Record · LEDGER

Super-Resolution Generative Adversarial Networks based Video Enhancement

As of 20 August 2026, this Paper Citation Record lists 49 of 49 outbound references and 0 inbound Pith citation observations for arXiv:2505.10589.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2505.10589 v4

Coverage vector

measured 49 of 49 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T21:30:11.096597Z

measured 49 of 49 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

49 of 49 outbound references displayed

  • verified exact0
  • verified fuzzy36
  • unresolved13
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 3f294e3f-351c-4642-91f0-f1ddb7f85596 · outbound

This paper cites Photo-realistic sin- gle image super-resolution using a gener- ative adversarial network.

Super-Resolution Generative Adversarial Networks based Video Enhancement Photo-realistic sin- gle image super-resolution using a gener- ative adversarial network

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:30:11.809317Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T21:30:10.868497Z digest=sha256:3eaaeeb9fece6819ee52e3d55c63cc5bb88295a48345ea5786f7cb6c4e7214f5

Observation 7eba4810-3158-418e-ab69-589826106916 · outbound

This paper cites an unresolved cited work.

Super-Resolution Generative Adversarial Networks based Video Enhancement Unresolved cited work

Reference 2

Resolution
unresolved
raw_fallback, observed 2026-08-15T21:30:11.792630Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T21:30:10.873823Z digest=sha256:e875d3dd3088d5fa3e07763588484fdfc511dec2167ab9164f2098594e4eca0b

Observation faa03265-6397-4214-8d1a-9150d563f156 · outbound

This paper cites Enhanc- ing space-time video super-resolution via spatial-temporal feature interaction, 2024.

Super-Resolution Generative Adversarial Networks based Video Enhancement Enhanc- ing space-time video super-resolution via spatial-temporal feature interaction, 2024

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:30:11.777667Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T21:30:10.878023Z digest=sha256:cd278825735e89c7c6647b2cbec4d9095d2dbeb86657686c2667f97f3aba2205

Observation 6cd06c85-6093-4f4c-b3b4-ca9f3cbf4be5 · outbound

This paper cites Image super- resolution using deep convolutional net- works, 2015.

Super-Resolution Generative Adversarial Networks based Video Enhancement Image super- resolution using deep convolutional net- works, 2015

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:30:11.764614Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T21:30:10.881995Z digest=sha256:d2d399fd7ed1828dce8ae6ff4f5b633698b3d1f82ffced44364f60287edba704

Observation 899417a6-4600-4cdb-aba1-d12f4501629f · outbound

This paper cites Non-local neural networks, 2018.

Super-Resolution Generative Adversarial Networks based Video Enhancement Non-local neural networks, 2018

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:30:11.752483Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T21:30:10.888821Z digest=sha256:d4dd015c091c7962968168ce8011fcf6b812a59dc6a1498aaacc6f5033e92311

Observation dd8daae9-accf-4e56-a66c-206d52ad1ab6 · outbound

This paper cites Deep residual learning for image recognition, 2015.

Super-Resolution Generative Adversarial Networks based Video Enhancement Deep residual learning for image recognition, 2015

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-15T21:30:10.893844Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:30:10.893844Z digest=sha256:ebb283b0b344eb256dd98fe3265368c93977cb52bbc5a2b6638e4e5ce8e76f73

Observation cec67a67-6b5c-4408-95a7-59d40ef9ae68 · outbound

This paper cites Gomez, Lukasz Kaiser, and Illia Polosukhin.

Super-Resolution Generative Adversarial Networks based Video Enhancement Gomez, Lukasz Kaiser, and Illia Polosukhin

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-15T21:30:10.898226Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:30:10.898226Z digest=sha256:517055d068122370aa698a48e35421d71b5a9b56094b004cc9ba2900a60653c3

Observation 62875cdb-0476-4b87-9bd8-30b05e4072e4 · outbound

This paper cites Perceptual losses for real-time style transfer and super-resolution, 2016.

Super-Resolution Generative Adversarial Networks based Video Enhancement Perceptual losses for real-time style transfer and super-resolution, 2016

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-15T21:30:10.902905Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:30:10.902905Z digest=sha256:b15824cbb75fbf719a0991d1923b92462f4364eda8c59866c90540254e1fa62d

Observation b1ed9647-a250-4618-8795-5c8d880b2785 · outbound

This paper cites Gradient variance loss for structure- enhanced image super-resolution, 2022.

Super-Resolution Generative Adversarial Networks based Video Enhancement Gradient variance loss for structure- enhanced image super-resolution, 2022

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:30:11.717008Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T21:30:10.907387Z digest=sha256:f178e624ace247ce3535e2ac4d5e6d3f9221e3942184e1474e89661d55053dae

Observation 4a11dcbb-d728-4bfd-9b9a-77987a12db76 · outbound

This paper cites Deep learning for sin- gle image super-resolution: A brief re- view.IEEE Transactions on Multimedia, 21(12):3106–3121, December 2019.

Super-Resolution Generative Adversarial Networks based Video Enhancement Deep learning for sin- gle image super-resolution: A brief re- view.IEEE Transactions on Multimedia, 21(12):3106–3121, December 2019

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:30:11.704463Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T21:30:10.912184Z digest=sha256:581e3dcdc13114685ad1b9ede3530d8ffc31fb2746173aa65c0f7ce6e6159b1f

Observation 78a9035c-231c-4801-ab60-176a2df87e53 · outbound

This paper cites Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde- Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio.

Super-Resolution Generative Adversarial Networks based Video Enhancement Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde- Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:30:11.689373Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T21:30:10.915993Z digest=sha256:45555ae367b34223341a11c5e4aeed126bacfc706ebbb0df8665459b04b9b261

Observation bb382528-9dfa-4e3a-b62d-2e09b0fb793a · outbound

This paper cites Generative adversarial networks for image super-resolution: A survey, 2024.

Super-Resolution Generative Adversarial Networks based Video Enhancement Generative adversarial networks for image super-resolution: A survey, 2024

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-15T21:30:10.920618Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:30:10.920618Z digest=sha256:31aa92387853597624f3f44c89bff1459b75ee5fc27f7817d561dc98928a53a9

Observation 4b383a5a-6953-48b2-92f0-523f970f238d · outbound

This paper cites Generative adversarialnetworksforsyntheticdatagen- eration: A comparative study, 12 2021.

Super-Resolution Generative Adversarial Networks based Video Enhancement Generative adversarialnetworksforsyntheticdatagen- eration: A comparative study, 12 2021

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:30:11.668705Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T21:30:10.925920Z digest=sha256:7ebdeaebe6ad38ffe7c80f4a3ac72a9c665535b531bdbb5e0f4fc4833dd5230a

Observation ad1a4aa7-be65-4c29-9992-e09f3cced146 · outbound

This paper cites Laploss: Laplacianpyramid-basedmultiscalelossfor image translation, 2025.

Super-Resolution Generative Adversarial Networks based Video Enhancement Laploss: Laplacianpyramid-basedmultiscalelossfor image translation, 2025

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:30:11.656171Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T21:30:10.931763Z digest=sha256:98f6af624c77cb0e6b4fa08f4d607706be1fb711fba61e8531668d05419b08a3

Observation 58649b6a-ae96-4731-a4d3-842a5fd8bc16 · outbound

This paper cites Weinberger.

Super-Resolution Generative Adversarial Networks based Video Enhancement Weinberger

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-15T21:30:10.936417Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:30:10.936417Z digest=sha256:f29a8ea4a9bb955900b393a962fa6f4af8ca3773f0cfd5f36dce9b7fe59ecf7e

Observation f38f7efb-bf71-4e84-982b-9d3d6c2326c9 · outbound

This paper cites Esrgan: Enhanced super-resolution generative ad- versarial networks, 2018.

Super-Resolution Generative Adversarial Networks based Video Enhancement Esrgan: Enhanced super-resolution generative ad- versarial networks, 2018

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:30:11.634150Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T21:30:10.941790Z digest=sha256:5f898cd34fce488dc8691321348885a87697c19832b7fe22879d38e9cedad24b

Observation 19429b46-eb67-4f33-ba86-b02be32cfa51 · outbound

This paper cites Empirical evaluation of rectified ac- tivations in convolutional network, 2015.

Super-Resolution Generative Adversarial Networks based Video Enhancement Empirical evaluation of rectified ac- tivations in convolutional network, 2015

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:30:11.621257Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T21:30:10.946225Z digest=sha256:7ad26b54eb37fd4aacdae88296018623bb83c50c9bbef98e04978675beaebe98

Observation 29a66de5-28df-4f56-ad14-57b7e3c2f7ba · outbound

This paper cites Residual network improves the prediction accuracy of genomic selection.Animal Ge- netics, 55:n/a–n/a, 05 2024.

Super-Resolution Generative Adversarial Networks based Video Enhancement Residual network improves the prediction accuracy of genomic selection.Animal Ge- netics, 55:n/a–n/a, 05 2024

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:30:11.609084Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T21:30:10.951801Z digest=sha256:524930cb1c136cf98cfb40dcabceb8681b3c0ff3598111d3e3f41d535c959e1f

Observation 348b0703-d2a7-4899-8bb8-ab7b10061790 · outbound

This paper cites Uni- fying nonlocal blocks for neural networks, 2021.

Super-Resolution Generative Adversarial Networks based Video Enhancement Uni- fying nonlocal blocks for neural networks, 2021

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:30:11.596015Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T21:30:10.956881Z digest=sha256:28bd6683e907c7adc482cb0f5c364ee2e9058d566945e55a95ba2d92ca2310e5

Observation c58319c0-45e7-4180-ab77-48717fa7d154 · outbound

This paper cites Efros, Eli Shechtman, and Oliver Wang.

Super-Resolution Generative Adversarial Networks based Video Enhancement Efros, Eli Shechtman, and Oliver Wang

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:30:11.583538Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T21:30:10.961407Z digest=sha256:da20eed8a4c6b4370ec2b0fd83225d704af051570bbbee47ad394bcd3c701971

Observation f1819b19-50ea-4ac5-8a77-0c155fc60d73 · outbound

This paper cites Understanding ssim, 2020.

Super-Resolution Generative Adversarial Networks based Video Enhancement Understanding ssim, 2020

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:30:11.567951Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T21:30:10.965992Z digest=sha256:73676e1ecc0297a61e1a2d3c3e5f8d3ee2aafecddc9fe0b22165abc99d9d32de

Observation c4062ac9-afb2-44e7-b990-21cce4dc71e9 · outbound

This paper cites Bvi- dvc: A training database for deep video compression.IEEE Transactions on Mul- timedia, 24:3847–3858, 2021.

Super-Resolution Generative Adversarial Networks based Video Enhancement Bvi- dvc: A training database for deep video compression.IEEE Transactions on Mul- timedia, 24:3847–3858, 2021

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:30:11.551509Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T21:30:10.970028Z digest=sha256:5ccc39945b35778865364e02d1759613fca9e30e28b6c220b2c32ad0679acca6

Observation 4151b9d0-0f45-4410-afb0-0104de3fc119 · outbound

This paper cites BVI-AOM: A New Training Dataset for Deep Video Compression Optimization.

Super-Resolution Generative Adversarial Networks based Video Enhancement BVI-AOM: A New Training Dataset for Deep Video Compression Optimization

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-15T21:30:10.973951Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:30:10.973951Z digest=sha256:ce263f5864770e2f30a8fe3def83557f2383c8662d533e12556e77e015847010

Observation f1aac45d-3f1d-4fd9-8998-be340662f6f1 · outbound

This paper cites Deep learning tech- niques for super-resolution in video games, 2020.

Super-Resolution Generative Adversarial Networks based Video Enhancement Deep learning tech- niques for super-resolution in video games, 2020

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:30:11.538587Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T21:30:10.978485Z digest=sha256:9e554cc19bc3286b23dc7f09b516bde22bfb378e39e1434458bfd0d1119794eb

Observation 746d2326-98b3-4130-9691-5f9955573c15 · outbound

This paper cites Extrapolation, interpola- tion, and smoothing of stationary time se- ries with engineering applications, 1949.

Super-Resolution Generative Adversarial Networks based Video Enhancement Extrapolation, interpola- tion, and smoothing of stationary time se- ries with engineering applications, 1949

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:30:11.525922Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T21:30:10.983004Z digest=sha256:504027271cc000c74b1416c8832f4516c1bbfac9d0394c5e275263fdd7eabb5f

Observation f9c5cb76-d627-4652-a818-ced0d2ad744a · outbound

This paper cites an unresolved cited work.

Super-Resolution Generative Adversarial Networks based Video Enhancement Unresolved cited work

Reference 26

Resolution
unresolved
raw_fallback, observed 2026-08-15T21:30:11.510208Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T21:30:10.987670Z digest=sha256:79e94b4f24b55a0d36c685cb3fd2983873973a74042d8186e33085111ab56dee

Observation 7fd86f6f-4df5-466c-8529-ad2b3e087bb6 · outbound

This paper cites an unresolved cited work.

Super-Resolution Generative Adversarial Networks based Video Enhancement Unresolved cited work

Reference 27

Resolution
unresolved
raw_fallback, observed 2026-08-15T21:30:11.496918Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T21:30:10.992077Z digest=sha256:b2f08513e9f1d54c0531f46594804d89058668a317155a62ba3789d506a13e97

Observation b0c74444-822b-4cf7-a7bb-c0c40ea66797 · outbound

This paper cites Interpolation and sharpening forimageupsampling.

Super-Resolution Generative Adversarial Networks based Video Enhancement Interpolation and sharpening forimageupsampling

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:30:11.482033Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T21:30:10.997549Z digest=sha256:5ab387ae14b04c3de771fc761909bd45287a9821c84c66178ee78443f8b48687

Observation 8a97944b-211d-484c-9c83-b51cfada6389 · outbound

This paper cites Freeman, T.R.

Super-Resolution Generative Adversarial Networks based Video Enhancement Freeman, T.R

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:30:11.468386Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T21:30:11.002288Z digest=sha256:c601452167ceda5dfe3519392a1878465020a8d56f924f4871404d847d6aee67

Observation 9f77c384-795f-4593-afc8-1f963ad4867e · outbound

This paper cites an unresolved cited work.

Super-Resolution Generative Adversarial Networks based Video Enhancement Unresolved cited work

Reference 30

Resolution
unresolved
raw_fallback, observed 2026-08-15T21:30:11.456397Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T21:30:11.006316Z digest=sha256:539153ea82c5214c6f849f501fcf4c65c079701c66a32ee59db16c44da66b949

Observation abebcb68-6bb2-41e5-aa99-c01d25584fd2 · outbound

This paper cites Yang, Wright J., Huang T.

Super-Resolution Generative Adversarial Networks based Video Enhancement Yang, Wright J., Huang T

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:30:11.442975Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T21:30:11.010786Z digest=sha256:da3a357a9c9b6d0a2c902c043acb0a0f1041af94addd3bf8805184694160ef5a

Observation a0853139-b8e2-4258-9f1b-fcdfa6b586ac · outbound

This paper cites Y., and Xiong Y.

Super-Resolution Generative Adversarial Networks based Video Enhancement Y., and Xiong Y

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:30:11.424141Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T21:30:11.014744Z digest=sha256:3da75d10004e4353168e39cd135fc90112eeb223814afe3611abb466a7144f8b

Observation d063142f-cc41-4e0a-8456-df9127a83607 · outbound

This paper cites an unresolved cited work.

Super-Resolution Generative Adversarial Networks based Video Enhancement Unresolved cited work

Reference 33

Resolution
unresolved
raw_fallback, observed 2026-08-15T21:30:11.410957Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T21:30:11.018617Z digest=sha256:14cd1f4c50a8121de0d0924c79be279ba1e1354cc0c70e67b4c3f375faf2586c

Observation 1663e633-a179-4a0b-9900-da4370f3607c · outbound

This paper cites Super- resolution from a single image, 2009.

Super-Resolution Generative Adversarial Networks based Video Enhancement Super- resolution from a single image, 2009

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:30:11.398552Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T21:30:11.023518Z digest=sha256:8788e96fcd4959b30ab4d89821cd2e5c064b3e2b81acc0de4b8d5726977043c3

Observation ca9a55cb-9ba6-4d67-92c8-1a43b464fe81 · outbound

This paper cites an unresolved cited work.

Super-Resolution Generative Adversarial Networks based Video Enhancement Unresolved cited work

Reference 35

Resolution
unresolved
raw_fallback, observed 2026-08-15T21:30:11.386511Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T21:30:11.027640Z digest=sha256:60db8139a71296aef81bb5dd3082d55a8bfd39a79908703613f7bf6dc35a84e4

Observation b8083215-770b-47bb-8c0e-53bc971c8874 · outbound

This paper cites Kamrul Hasan, Shid- harthoRoy, Md.AshrafulAlam, EklasHos- sain, and Mohiuddin Ahmad.

Super-Resolution Generative Adversarial Networks based Video Enhancement Kamrul Hasan, Shid- harthoRoy, Md.AshrafulAlam, EklasHos- sain, and Mohiuddin Ahmad

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:30:11.372683Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T21:30:11.032511Z digest=sha256:61240e22d033bfb635eef0d9976265dfc63917f9d4960abccc9d92500e48871b

Observation 08fd4b01-f386-4693-9a71-c19217851ac0 · outbound

This paper cites U-net: Convolutional net- works for biomedical image segmentation, 2015.

Super-Resolution Generative Adversarial Networks based Video Enhancement U-net: Convolutional net- works for biomedical image segmentation, 2015

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:30:11.360006Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T21:30:11.037988Z digest=sha256:646bcdb2b8006936a6256ef2e14a8f98163acc204c8afa64ba227126153f1ac5

Observation 6c1a23a1-0b89-4385-9c1d-06f4e23218e2 · outbound

This paper cites A u-net based discriminator for generative adversarial networks, 06 2020.

Super-Resolution Generative Adversarial Networks based Video Enhancement A u-net based discriminator for generative adversarial networks, 06 2020

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:30:11.345785Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T21:30:11.043420Z digest=sha256:d390454e27dcff6e5655c8cddd869e175bc174cc7a0735ccdbec417b1901439c

Observation ec9664ab-8d3e-4209-8f43-06436a8c8bb8 · outbound

This paper cites Frequency-domain data augmenta- tion of vibration data for fault diagno- sis using deep neural networks.

Super-Resolution Generative Adversarial Networks based Video Enhancement Frequency-domain data augmenta- tion of vibration data for fault diagno- sis using deep neural networks

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:30:11.330214Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T21:30:11.052841Z digest=sha256:3058ea0724923bb7cd3d192fe5bdf959e0484bd9ccd55ba0bbb7c59499dc2ab8

Observation 1cd6cd82-84a5-4e9b-88ad-4fe64d102259 · outbound

This paper cites Wavelet elm-ae based data augmentation and deep learning for efficient emotion recognition using eeg recordings.IEEE Access, 10:72171–72181, 2022.

Super-Resolution Generative Adversarial Networks based Video Enhancement Wavelet elm-ae based data augmentation and deep learning for efficient emotion recognition using eeg recordings.IEEE Access, 10:72171–72181, 2022

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:30:11.312521Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T21:30:11.057350Z digest=sha256:2807628a371e8c86db94901f614330b4cb1c702c1428b9100acae95a8056ede0

Observation 8eaf8fbc-165c-4b7c-a1d0-14591c1d2879 · outbound

This paper cites Rethinking data augmentation for image super-resolution: A comprehensive analysis and a new strategy, 2020.

Super-Resolution Generative Adversarial Networks based Video Enhancement Rethinking data augmentation for image super-resolution: A comprehensive analysis and a new strategy, 2020

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:30:11.297573Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T21:30:11.061578Z digest=sha256:2683a66797ca42393078c489a3631cda54d1a269af7085905be62a22fb8c8179

Observation d1ea3f64-691c-4aff-9978-67bcd091c030 · outbound

This paper cites Efficient blind super-resolution imaging via adaptive degradation-aware estimation.Knowledge- Based Systems, 297:111973, 2024.

Super-Resolution Generative Adversarial Networks based Video Enhancement Efficient blind super-resolution imaging via adaptive degradation-aware estimation.Knowledge- Based Systems, 297:111973, 2024

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:30:11.282388Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T21:30:11.065821Z digest=sha256:24775e1e3e5ba69940bbd5a1add44e00a154c6bd22ee4ce3d2730d6e3e24fb79

Observation a1dcc48d-347a-4b35-969a-22971a575360 · outbound

This paper cites an unresolved cited work.

Super-Resolution Generative Adversarial Networks based Video Enhancement Unresolved cited work

Reference 43

Resolution
unresolved
raw_fallback, observed 2026-08-15T21:30:11.262418Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T21:30:11.069794Z digest=sha256:a86ec2279dc995bac105cb316f2c91a7d191f94509e6351282237b76de8277a2

Observation cfa630c4-d111-470f-a67b-cfe5c5776bea · outbound

This paper cites Cubuk, Barret Zoph, Justin Gilmer, and Balaji Lakshminarayanan.

Super-Resolution Generative Adversarial Networks based Video Enhancement Cubuk, Barret Zoph, Justin Gilmer, and Balaji Lakshminarayanan

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:30:11.241647Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T21:30:11.074119Z digest=sha256:e8d3c0a157b61cca1e895f9c2168972c3c6840afef872959fed5f451ae95c440

Observation 910f4848-9409-4cbb-aec5-eae846ee7ab0 · outbound

This paper cites Ct-scan de- noising using a charbonnier loss genera- tive adversarial network.IEEE Access, 9:84093–84109, 2021.

Super-Resolution Generative Adversarial Networks based Video Enhancement Ct-scan de- noising using a charbonnier loss genera- tive adversarial network.IEEE Access, 9:84093–84109, 2021

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:30:11.221250Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T21:30:11.078536Z digest=sha256:136ed7881d9bc73d4ab99c9998cb79696d45af7e92884d5b32a546b7cd826c33

Observation c806741a-9de6-4b01-92ac-700d4e558c21 · outbound

This paper cites Spa- tio temporal forest fire spread modeling us- ing cellular automata honey bee foraging and gis.Bulletin of Environment, Phar- macology and Life Sciences, 3:201–214, 12 2013.

Super-Resolution Generative Adversarial Networks based Video Enhancement Spa- tio temporal forest fire spread modeling us- ing cellular automata honey bee foraging and gis.Bulletin of Environment, Phar- macology and Life Sciences, 3:201–214, 12 2013

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:30:11.198441Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T21:30:11.082750Z digest=sha256:aca66f17cd54293f2080589e13b2e840117564fb0cff566536194d7de1c992f3

Observation 1981d522-5099-43c9-88dc-de74d0667a17 · outbound

This paper cites Single image deblurring based on auxiliary sobel loss function.

Super-Resolution Generative Adversarial Networks based Video Enhancement Single image deblurring based on auxiliary sobel loss function

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:30:11.185149Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T21:30:11.086635Z digest=sha256:bb561a71f4dbe27e41e7e9d2e918af7492b73dbd7cb547f9af4d7cb848b5209d

Observation 2e0c2bc6-696e-4067-83a0-3cf7045d2727 · outbound

This paper cites Wavelet transforma- tions and its applications in digital image processing, 10 2023.

Super-Resolution Generative Adversarial Networks based Video Enhancement Wavelet transforma- tions and its applications in digital image processing, 10 2023

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:30:11.170633Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T21:30:11.091355Z digest=sha256:5bed40bd66bc386712144506c8c3e2bdf6fdb809dba7e51450d73c7a3790da06

Observation 52d421d3-cb35-4ca2-990d-1ae74d5e46bf · outbound

This paper cites Design of fir filters for fast multiscale directional filter banks.Interna- tional Journal of u- and e-Service, Science and Technology, 7, 10 2014.

Super-Resolution Generative Adversarial Networks based Video Enhancement Design of fir filters for fast multiscale directional filter banks.Interna- tional Journal of u- and e-Service, Science and Technology, 7, 10 2014

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:30:11.150672Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T21:30:11.096597Z digest=sha256:d176749587a9d91fb043e629915c216dc0580c09b4f15e73772aa7d70d1fcf4e

Pith citing papers

No inbound Pith citation observations are available.