Paper Citation Record · LEDGER

Dual Attention Residual U-Net for Accurate Brain Ultrasound Segmentation in IVH Detection

As of 8 August 2026, this Paper Citation Record lists 42 of 42 outbound references and 0 inbound Pith citation observations for arXiv:2505.17683.

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

pith.paper-citation-record.v1
2505.17683 v2

Coverage vector

measured 42 of 42 reference resolution

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measured 42 of 42 standing notices

One-hop event checks from named stored sources.

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measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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

Source: cited_works

Reference resolution

42 of 42 outbound references displayed

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External citation measurements

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Outbound references

Observation 74b47ab9-1215-4f1e-b7a9-0bc71bac0c75 · outbound

This paper cites A Study on ReLU and Softmax in Transformer.

Dual Attention Residual U-Net for Accurate Brain Ultrasound Segmentation in IVH Detection A Study on ReLU and Softmax in Transformer

Reference 2

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Observation d675d8be-38d2-4bc4-a9f9-23fab2009337 · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale,.

Dual Attention Residual U-Net for Accurate Brain Ultrasound Segmentation in IVH Detection An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:44:57.568786Z

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Observation ad62977a-1cd7-4bab-8647-918ca966a4f4 · outbound

This paper cites Sparse Attention with Linear Units.

Dual Attention Residual U-Net for Accurate Brain Ultrasound Segmentation in IVH Detection Sparse Attention with Linear Units

Reference 4

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Observation bba92d16-d264-4898-9f1b-0483f5381b16 · outbound

This paper cites UNet 3+: A Full-Scale Con- nected UNet for Medical Image Segmentation,.

Dual Attention Residual U-Net for Accurate Brain Ultrasound Segmentation in IVH Detection UNet 3+: A Full-Scale Con- nected UNet for Medical Image Segmentation,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:44:57.255415Z

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This paper cites A comparative study of pre-trained convolutional neural networks for se- mantic segmentation of breast tumors in ultra- sound,.

Dual Attention Residual U-Net for Accurate Brain Ultrasound Segmentation in IVH Detection A comparative study of pre-trained convolutional neural networks for se- mantic segmentation of breast tumors in ultra- sound,

Reference 6

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Observation 6427bda2-45bb-4aff-86ff-c2574937b9c1 · outbound

This paper cites SegNet: A Deep Con- volutional Encoder-Decoder Architecture for Im- age Segmentation,.

Dual Attention Residual U-Net for Accurate Brain Ultrasound Segmentation in IVH Detection SegNet: A Deep Con- volutional Encoder-Decoder Architecture for Im- age Segmentation,

Reference 7

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Observation 60fda836-6a5d-4b6f-8d36-e4271c87965a · outbound

This paper cites Attention U-Net: Learning Where to Look for the Pancreas.

Dual Attention Residual U-Net for Accurate Brain Ultrasound Segmentation in IVH Detection Attention U-Net: Learning Where to Look for the Pancreas

Reference 8

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Observation c3ce3d3d-c1fe-4fee-a018-6f210f986d21 · outbound

This paper cites Road Extraction by Deep Residual U-Net,.

Dual Attention Residual U-Net for Accurate Brain Ultrasound Segmentation in IVH Detection Road Extraction by Deep Residual U-Net,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:44:56.566309Z

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Observation 55b5f75e-e24e-45e4-8187-7ce77096cc45 · outbound

This paper cites Spatial and Channel Attention Modulated Network for Medical Image Segmen- tation,.

Dual Attention Residual U-Net for Accurate Brain Ultrasound Segmentation in IVH Detection Spatial and Channel Attention Modulated Network for Medical Image Segmen- tation,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:44:56.364426Z

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Observation 7fd8657c-2583-4728-b9ec-70bea1673b83 · outbound

This paper cites Squeeze-and-Excitation Net- works,.

Dual Attention Residual U-Net for Accurate Brain Ultrasound Segmentation in IVH Detection Squeeze-and-Excitation Net- works,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:44:56.203621Z

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Observation 980a2d99-e5c7-43a7-ada2-c06231efbcec · outbound

This paper cites GC-Net: Global Context Net- work for Medical Image Segmentation,.

Dual Attention Residual U-Net for Accurate Brain Ultrasound Segmentation in IVH Detection GC-Net: Global Context Net- work for Medical Image Segmentation,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:44:56.037248Z

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Observation 38594d31-492d-410e-a26d-a11f680cac03 · outbound

This paper cites MDA-Unet: A Multi-Scale Di- lated Attention U-Net for Medical Image Seg- mentation,.

Dual Attention Residual U-Net for Accurate Brain Ultrasound Segmentation in IVH Detection MDA-Unet: A Multi-Scale Di- lated Attention U-Net for Medical Image Seg- mentation,

Reference 13

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Observation 82f5c897-97cf-415c-b54d-c6e2ef005055 · outbound

This paper cites FCPFNet: Feature Complementa- tion Network with Pyramid Fusion for Semantic Segmentation,.

Dual Attention Residual U-Net for Accurate Brain Ultrasound Segmentation in IVH Detection FCPFNet: Feature Complementa- tion Network with Pyramid Fusion for Semantic Segmentation,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:44:55.632987Z

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Observation a0d506cc-7893-4d1a-bfd9-e7b29aa01658 · outbound

This paper cites U-Net: Convolutional Networks for Biomedical Image Segmentation,.

Dual Attention Residual U-Net for Accurate Brain Ultrasound Segmentation in IVH Detection U-Net: Convolutional Networks for Biomedical Image Segmentation,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:44:55.468448Z

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Observation afd9c09a-c141-438b-b8f0-18a31d82ddd7 · outbound

This paper cites UNet++: A Nested U-Net Ar- chitecture for Medical Image Segmentation,.

Dual Attention Residual U-Net for Accurate Brain Ultrasound Segmentation in IVH Detection UNet++: A Nested U-Net Ar- chitecture for Medical Image Segmentation,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:44:55.315356Z

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Observation a20a803c-af1d-4556-a579-bc05c8d1cca1 · outbound

This paper cites V-Net: Fully Convolutional Neural Networks for Volumetric Medical Im- age Segmentation,.

Dual Attention Residual U-Net for Accurate Brain Ultrasound Segmentation in IVH Detection V-Net: Fully Convolutional Neural Networks for Volumetric Medical Im- age Segmentation,

Reference 17

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Observation 1659d5fb-8f49-438e-9411-e24990fa9030 · outbound

This paper cites Axial-DeepLab: Stand-Alone Axial-Attention for Panoptic Segmentation.

Dual Attention Residual U-Net for Accurate Brain Ultrasound Segmentation in IVH Detection Axial-DeepLab: Stand-Alone Axial-Attention for Panoptic Segmentation

Reference 18

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This paper cites Deep Learning in Medical Ultrasound Image Segmentation: a Review.

Dual Attention Residual U-Net for Accurate Brain Ultrasound Segmentation in IVH Detection Deep Learning in Medical Ultrasound Image Segmentation: a Review

Reference 19

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Observation 5f3e5c3a-fac2-4f5a-94d2-ae91e5fb848d · outbound

This paper cites Convolutional neu- ral networks in medical image understanding: a survey,.

Dual Attention Residual U-Net for Accurate Brain Ultrasound Segmentation in IVH Detection Convolutional neu- ral networks in medical image understanding: a survey,

Reference 20

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Observation 5c52407e-cdcc-4ad2-82d0-bbca3998bd84 · outbound

This paper cites MRL-Net: Multi-Scale Represen- tation Learning Network for COVID-19 Lung CT Image Segmentation,.

Dual Attention Residual U-Net for Accurate Brain Ultrasound Segmentation in IVH Detection MRL-Net: Multi-Scale Represen- tation Learning Network for COVID-19 Lung CT Image Segmentation,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:44:54.758330Z

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Observation ba64c2d3-28d6-45cd-aa2d-aea0f189c202 · outbound

This paper cites IMAGPose: A Unified Conditional Framework for Pose-Guided Person Generation,.

Dual Attention Residual U-Net for Accurate Brain Ultrasound Segmentation in IVH Detection IMAGPose: A Unified Conditional Framework for Pose-Guided Person Generation,

Reference 22

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Observation a1d7e108-2be6-46db-9c83-ea112ddf8213 · outbound

This paper cites IMAGDressing-v1: Customizable Virtual Dressing,.

Dual Attention Residual U-Net for Accurate Brain Ultrasound Segmentation in IVH Detection IMAGDressing-v1: Customizable Virtual Dressing,

Reference 23

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Observation 2160c1cd-3721-4840-adb3-a358804bbf04 · outbound

This paper cites A Deep Feature Selection Method for Tumor Classification in Breast Ul- trasound Images,.

Dual Attention Residual U-Net for Accurate Brain Ultrasound Segmentation in IVH Detection A Deep Feature Selection Method for Tumor Classification in Breast Ul- trasound Images,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:44:54.251149Z

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Observation 86a682fc-0e39-4d9a-8063-f021390d32e3 · outbound

This paper cites KiU-Net: Towards Accurate Segmentation of Biomedical Images using Over- complete Representations,.

Dual Attention Residual U-Net for Accurate Brain Ultrasound Segmentation in IVH Detection KiU-Net: Towards Accurate Segmentation of Biomedical Images using Over- complete Representations,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:44:54.109434Z

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Observation 465d6a56-498e-4835-8a1a-86f53f05aa25 · outbound

This paper cites DAU-Net: Dual attention- aided U-Net for segmenting tumor in breast ul- trasound images,.

Dual Attention Residual U-Net for Accurate Brain Ultrasound Segmentation in IVH Detection DAU-Net: Dual attention- aided U-Net for segmenting tumor in breast ul- trasound images,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:44:53.881286Z

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Observation 1008d956-9388-48e4-b814-ccaf9ce9cbd9 · outbound

This paper cites Learning to Segment Brain Anatomy from 2D Ultrasound with Less Data,.

Dual Attention Residual U-Net for Accurate Brain Ultrasound Segmentation in IVH Detection Learning to Segment Brain Anatomy from 2D Ultrasound with Less Data,

Reference 27

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Observation d0c3f71f-2f29-476e-8aca-20dc9518cfb9 · outbound

This paper cites Weighted Res-UNet for High- Quality Retina Vessel Segmentation,.

Dual Attention Residual U-Net for Accurate Brain Ultrasound Segmentation in IVH Detection Weighted Res-UNet for High- Quality Retina Vessel Segmentation,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:44:53.486182Z

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This paper cites Attention-Enriched Deep Learning Model for Breast Tumor Segmentation in Ultrasound Images,.

Dual Attention Residual U-Net for Accurate Brain Ultrasound Segmentation in IVH Detection Attention-Enriched Deep Learning Model for Breast Tumor Segmentation in Ultrasound Images,

Reference 29

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Observation d43579b5-d3d1-470a-b21d-da87bcad9e01 · outbound

This paper cites Automatic real-time CNN-based neonatal brain ventricles segmentation,.

Dual Attention Residual U-Net for Accurate Brain Ultrasound Segmentation in IVH Detection Automatic real-time CNN-based neonatal brain ventricles segmentation,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:44:53.133646Z

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Observation c4604536-1727-42f4-af65-8bc40178f599 · outbound

This paper cites Born Too soon: the global epi- demiology of 15 million preterm births,.

Dual Attention Residual U-Net for Accurate Brain Ultrasound Segmentation in IVH Detection Born Too soon: the global epi- demiology of 15 million preterm births,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:44:53.004424Z

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This paper cites AAU-net: An Adaptive At- tention U-net for Breast Lesions Segmentation in Ultrasound Images,.

Dual Attention Residual U-Net for Accurate Brain Ultrasound Segmentation in IVH Detection AAU-net: An Adaptive At- tention U-net for Breast Lesions Segmentation in Ultrasound Images,

Reference 32

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This paper cites CBAM: Convolutional Block At- tention Module,.

Dual Attention Residual U-Net for Accurate Brain Ultrasound Segmentation in IVH Detection CBAM: Convolutional Block At- tention Module,

Reference 33

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Observation 2fcf63cc-fd45-41d6-b592-8b6cb08bd9b2 · outbound

This paper cites An improved resnet algorithm based on cbam,.

Dual Attention Residual U-Net for Accurate Brain Ultrasound Segmentation in IVH Detection An improved resnet algorithm based on cbam,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:44:52.503809Z

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Observation 82554944-c4bb-49b7-bf26-5799485f6134 · outbound

This paper cites Neonatal posthemorrhagic hydrocephalus from prematurity: Pathophysiol- ogy and current treatment concepts: A review,.

Dual Attention Residual U-Net for Accurate Brain Ultrasound Segmentation in IVH Detection Neonatal posthemorrhagic hydrocephalus from prematurity: Pathophysiol- ogy and current treatment concepts: A review,

Reference 35

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Observation 1be49203-8f3d-4092-a6d3-3819d3a45393 · outbound

This paper cites Adapt or Perish: Adap- tive Sparse Transformer with Attentive Feature Refinement for Image Restoration,.

Dual Attention Residual U-Net for Accurate Brain Ultrasound Segmentation in IVH Detection Adapt or Perish: Adap- tive Sparse Transformer with Attentive Feature Refinement for Image Restoration,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:44:52.222833Z

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Observation f536f5f9-f603-4487-b690-d1495c7e607d · outbound

This paper cites IMAGGarment: Fine-Grained Garment Generation for Controllable Fashion Design.

Dual Attention Residual U-Net for Accurate Brain Ultrasound Segmentation in IVH Detection IMAGGarment: Fine-Grained Garment Generation for Controllable Fashion Design

Reference 37

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This paper cites Long-Term TalkingFace Generation via Motion-Prior Conditional Diffusion Model.

Dual Attention Residual U-Net for Accurate Brain Ultrasound Segmentation in IVH Detection Long-Term TalkingFace Generation via Motion-Prior Conditional Diffusion Model

Reference 38

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This paper cites A Bag of Tricks for Fine-Grained Roof Extrac- tion,.

Dual Attention Residual U-Net for Accurate Brain Ultrasound Segmentation in IVH Detection A Bag of Tricks for Fine-Grained Roof Extrac- tion,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:44:52.098795Z

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Observation d849a8dc-0ebd-49c3-ac53-24230e20b1d0 · outbound

This paper cites Enhancing Land- slide Segmentation with Guide Attention Mech- anism and Fast Fourier Transformer,.

Dual Attention Residual U-Net for Accurate Brain Ultrasound Segmentation in IVH Detection Enhancing Land- slide Segmentation with Guide Attention Mech- anism and Fast Fourier Transformer,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:44:51.935321Z

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Observation 7251d311-ded6-48c0-b50b-1b412ce8e50c · outbound

This paper cites Advancing Pose-Guided Image Synthesis with Progressive Conditional Diffusion Models.

Dual Attention Residual U-Net for Accurate Brain Ultrasound Segmentation in IVH Detection Advancing Pose-Guided Image Synthesis with Progressive Conditional Diffusion Models

Reference 41

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Observation c3f0e9f3-7980-44c9-92a0-7d3dea495353 · outbound

This paper cites Classifying Breast Cancer Histopathological Images Using a Robust Artifi- cial Neural Network Architecture,.

Dual Attention Residual U-Net for Accurate Brain Ultrasound Segmentation in IVH Detection Classifying Breast Cancer Histopathological Images Using a Robust Artifi- cial Neural Network Architecture,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:44:51.807383Z

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Observation 5a265c24-7004-4e3c-a24c-17cd68debe47 · outbound

This paper cites Multiscale U-Net with Spatial Po- sitional Attention for Retinal Vessel Segmenta- tion,.

Dual Attention Residual U-Net for Accurate Brain Ultrasound Segmentation in IVH Detection Multiscale U-Net with Spatial Po- sitional Attention for Retinal Vessel Segmenta- tion,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:44:51.686836Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Pith citing papers

No inbound Pith citation observations are available.