Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-06T20:18:17.334955Z
Paper Citation Record · LEDGER
As of 12 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 0 inbound Pith citation observations for arXiv:2507.03341.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-06T20:18:17.334955Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
38 of 38 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation d0ea0e4d-3829-4d8c-adcb-ffc19bf16d68 · outbound
UltraDfeGAN: Detail-Enhancing Generative Adversarial Networks for High-Fidelity Functional Ultrasound Synthesis Nature communications 10(1), 1400 (2019)
Reference 1
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Observation 975e3668-aab5-46b4-99d1-37bae2ab0ed4 · outbound
UltraDfeGAN: Detail-Enhancing Generative Adversarial Networks for High-Fidelity Functional Ultrasound Synthesis Nature methods19(8), 1004–1012 (2022)
Reference 2
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Observation 978663a1-5452-46c8-9569-af0514fc5575 · outbound
UltraDfeGAN: Detail-Enhancing Generative Adversarial Networks for High-Fidelity Functional Ultrasound Synthesis Proceedings of the National Academy of Sciences 117(25), 14453–14463 (2020) Detail-Enhancing Generative Adversarial Networks 11
Reference 3
Source-reported events for the cited work
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Observation 79d6ca7e-2e56-4c0c-a16e-a53ee0718f60 · outbound
UltraDfeGAN: Detail-Enhancing Generative Adversarial Networks for High-Fidelity Functional Ultrasound Synthesis Nature Protocols 16(7), 3547–3571 (2021)
Reference 4
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Observation eccf6a73-c041-48f2-8073-60a6978b5bd1 · outbound
UltraDfeGAN: Detail-Enhancing Generative Adversarial Networks for High-Fidelity Functional Ultrasound Synthesis Nature communications 12(1), 1080 (2021)
Reference 5
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Observation 18f55d78-8eed-4ae3-b458-592f951289bf · outbound
UltraDfeGAN: Detail-Enhancing Generative Adversarial Networks for High-Fidelity Functional Ultrasound Synthesis Science translational medicine9(411), eaah6756 (2017)
Reference 6
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Observation 36f931df-faab-4cc3-9e91-a582b1bf9c06 · outbound
UltraDfeGAN: Detail-Enhancing Generative Adversarial Networks for High-Fidelity Functional Ultrasound Synthesis In: 2016 IEEE International Ultrasonics Symposium (IUS)
Reference 7
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Observation cc0270e7-8a63-4f9a-8a88-da8cf3e4a44a · outbound
UltraDfeGAN: Detail-Enhancing Generative Adversarial Networks for High-Fidelity Functional Ultrasound Synthesis Unresolved cited work
Reference 8
Source-reported events for the cited work
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Observation 4afe04dd-c47c-418c-a533-e513a60a2dcf · outbound
UltraDfeGAN: Detail-Enhancing Generative Adversarial Networks for High-Fidelity Functional Ultrasound Synthesis Frontiers in neuroscience13, 1384 (2020)
Reference 9
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Observation 696955b6-0e6d-4b9d-a28e-81343704a95e · outbound
UltraDfeGAN: Detail-Enhancing Generative Adversarial Networks for High-Fidelity Functional Ultrasound Synthesis Unresolved cited work
Reference 10
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Observation 042c7450-eff9-48ba-8896-f553878da392 · outbound
UltraDfeGAN: Detail-Enhancing Generative Adversarial Networks for High-Fidelity Functional Ultrasound Synthesis Nature Neuroscience27(1), 196–207 (2024)
Reference 11
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Observation c8acd450-ef89-435f-9f2b-a2bf693e00cf · outbound
UltraDfeGAN: Detail-Enhancing Generative Adversarial Networks for High-Fidelity Functional Ultrasound Synthesis Re- search 6, 0200 (2023)
Reference 12
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Observation 3720be5c-ece2-4a66-b36d-fa0f5f619be3 · outbound
UltraDfeGAN: Detail-Enhancing Generative Adversarial Networks for High-Fidelity Functional Ultrasound Synthesis Neuron112(10), 1710–1722 (2024)
Reference 13
Source-reported events for the cited work
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Observation d254e1e5-24bd-44a1-ae3e-b8b686995dc1 · outbound
UltraDfeGAN: Detail-Enhancing Generative Adversarial Networks for High-Fidelity Functional Ultrasound Synthesis Advances in neural in- formation processing systems27 (2014)
Reference 14
Source-reported events for the cited work
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Observation 7faf0b86-e9c1-4dfe-84e9-280b29a5a952 · outbound
UltraDfeGAN: Detail-Enhancing Generative Adversarial Networks for High-Fidelity Functional Ultrasound Synthesis Science Trans- lational Medicine 16(749), eadj3143 (2024)
Reference 15
Source-reported events for the cited work
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Observation 8921de31-d8a9-4c67-9642-7d9d0d640000 · outbound
UltraDfeGAN: Detail-Enhancing Generative Adversarial Networks for High-Fidelity Functional Ultrasound Synthesis Brain imaging and behavior15, 276–287 (2021)
Reference 16
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Observation 8ff084f6-057b-43ab-8d75-fb2d88b563a6 · outbound
UltraDfeGAN: Detail-Enhancing Generative Adversarial Networks for High-Fidelity Functional Ultrasound Synthesis Unresolved cited work
Reference 17
Source-reported events for the cited work
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Observation c2c155e5-0a03-4bfb-9c9a-efe61b82e440 · outbound
UltraDfeGAN: Detail-Enhancing Generative Adversarial Networks for High-Fidelity Functional Ultrasound Synthesis In: 2018 International conference on artificial intelligence and big data (ICAIBD)
Reference 18
Source-reported events for the cited work
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Observation 64aaefc9-9ca4-4a6b-a2a1-04c09b435270 · outbound
UltraDfeGAN: Detail-Enhancing Generative Adversarial Networks for High-Fidelity Functional Ultrasound Synthesis Scientific Reports13(1), 12098 (2023)
Reference 19
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Observation 06f8c028-97e3-40c1-be91-fe7f61c2d4c0 · outbound
UltraDfeGAN: Detail-Enhancing Generative Adversarial Networks for High-Fidelity Functional Ultrasound Synthesis Procedia computer science111, 17–23 (2017)
Reference 20
Source-reported events for the cited work
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Observation ac53dab8-c8af-4693-9873-c425e4b8bfef · outbound
UltraDfeGAN: Detail-Enhancing Generative Adversarial Networks for High-Fidelity Functional Ultrasound Synthesis Unresolved cited work
Reference 21
Source-reported events for the cited work
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Observation 9a83d1d5-884f-4836-97d5-8d67753b19d2 · outbound
UltraDfeGAN: Detail-Enhancing Generative Adversarial Networks for High-Fidelity Functional Ultrasound Synthesis Unresolved cited work
Reference 22
Source-reported events for the cited work
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Observation 84006c1a-41d7-458c-b6db-3baf27e4a8f4 · outbound
UltraDfeGAN: Detail-Enhancing Generative Adversarial Networks for High-Fidelity Functional Ultrasound Synthesis Deep learning applications pp
Reference 23
Source-reported events for the cited work
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Observation 9a28fe98-a6d3-45af-a8f4-c5cc803b4b44 · outbound
UltraDfeGAN: Detail-Enhancing Generative Adversarial Networks for High-Fidelity Functional Ultrasound Synthesis IEEE Transactions on Circuits and Systems for Video Technology (2025)
Reference 24
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Observation 88adbb9f-056d-4fea-aba8-c620c38ad339 · outbound
UltraDfeGAN: Detail-Enhancing Generative Adversarial Networks for High-Fidelity Functional Ultrasound Synthesis IEEE Transactions on Neural Systems and Rehabilitation Engineering31, 4601–4612 (2023)
Reference 25
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Observation 8dd12e55-afbf-4605-9bd4-608463ce4527 · outbound
UltraDfeGAN: Detail-Enhancing Generative Adversarial Networks for High-Fidelity Functional Ultrasound Synthesis IEEE Transactions on Cybernetics54(6), 3652–3665 (2024)
Reference 26
Source-reported events for the cited work
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Observation a0981bb0-4c68-4f25-ae93-f88bbc5ab74a · outbound
UltraDfeGAN: Detail-Enhancing Generative Adversarial Networks for High-Fidelity Functional Ultrasound Synthesis In: Pattern Recognition and Computer Vision: 4th Chinese Conference, PRCV 2021, Beijing, China, October 29–November 1, 2021, Proceedings, Part III 4
Reference 27
Source-reported events for the cited work
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Observation 721dba0e-520d-4b48-ac65-dc62e464c2a6 · outbound
UltraDfeGAN: Detail-Enhancing Generative Adversarial Networks for High-Fidelity Functional Ultrasound Synthesis In: Medical imaging with deep learning (2022)
Reference 28
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Observation bb960909-7336-40be-8fde-3fe7a1276bb6 · outbound
UltraDfeGAN: Detail-Enhancing Generative Adversarial Networks for High-Fidelity Functional Ultrasound Synthesis In: Pattern Recognition and Computer Vision: 4th Chinese Conference, PRCV 2021, Beijing, China, October 29–November 1, 2021, Proceedings, Part III 4
Reference 29
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 72497445-0a16-4601-9222-0798030dfb7a · outbound
UltraDfeGAN: Detail-Enhancing Generative Adversarial Networks for High-Fidelity Functional Ultrasound Synthesis IEEE Transactions on Pattern Analysis and Machine Intelligence (2024)
Reference 30
Source-reported events for the cited work
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Observation 9e6bd4fa-503a-4a89-b6cd-a9a1d8bef0e0 · outbound
UltraDfeGAN: Detail-Enhancing Generative Adversarial Networks for High-Fidelity Functional Ultrasound Synthesis Unresolved cited work
Reference 31
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Observation 000d8eb8-5122-427a-b71d-ad2929dadd23 · outbound
UltraDfeGAN: Detail-Enhancing Generative Adversarial Networks for High-Fidelity Functional Ultrasound Synthesis IEEE Transactions on Cybernetics54(9), 5026–5039 (2024) Detail-Enhancing Generative Adversarial Networks 13
Reference 32
Source-reported events for the cited work
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Observation 908b2982-46ff-4d8a-893a-6baa47565a4e · outbound
UltraDfeGAN: Detail-Enhancing Generative Adversarial Networks for High-Fidelity Functional Ultrasound Synthesis IEEE Transactions on Neural Systems and Rehabilitation Engineering31, 4017– 4028 (2023)
Reference 33
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Observation bfbb7307-8f04-47e3-9b85-1cad0e66ec7d · outbound
UltraDfeGAN: Detail-Enhancing Generative Adversarial Networks for High-Fidelity Functional Ultrasound Synthesis Unresolved cited work
Reference 34
Source-reported events for the cited work
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Observation fc5c5f9c-bb8d-4400-af77-026e324de654 · outbound
UltraDfeGAN: Detail-Enhancing Generative Adversarial Networks for High-Fidelity Functional Ultrasound Synthesis Large Scale GAN Training for High Fidelity Natural Image Synthesis
Reference 35
Source-reported events for the cited work
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Observation ee11e284-8792-454e-903f-006914a15e9f · outbound
UltraDfeGAN: Detail-Enhancing Generative Adversarial Networks for High-Fidelity Functional Ultrasound Synthesis In: ACM SIGGRAPH 2022 conference proceedings
Reference 36
Source-reported events for the cited work
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Observation 524acdae-8e86-4b37-a536-90fc9e534ecc · outbound
UltraDfeGAN: Detail-Enhancing Generative Adversarial Networks for High-Fidelity Functional Ultrasound Synthesis Vector-quantized Image Modeling with Improved VQGAN
Reference 37
Source-reported events for the cited work
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Observation d4fb18bd-141a-440b-8b51-06ed439647e6 · outbound
UltraDfeGAN: Detail-Enhancing Generative Adversarial Networks for High-Fidelity Functional Ultrasound Synthesis In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition
Reference 38
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
No inbound Pith citation observations are available.