Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-06T14:37:28.123398Z
Paper Citation Record · LEDGER
SemiSegECG: A Multi-Dataset Benchmark for Semi-Supervised Semantic Segmentation in ECG Delineation
As of 9 August 2026, this Paper Citation Record lists 44 of 44 outbound references and 0 inbound Pith citation observations for arXiv:2507.18323.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+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
Reference resolution
44 of 44 outbound references displayed
- verified exact1
- verified fuzzy37
- unresolved6
- parse uncertain0
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External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 193affc2-bb11-40f0-a13d-169cb876a632 · outbound
This paper cites Isp ecg delineation dataset, 2024.
SemiSegECG: A Multi-Dataset Benchmark for Semi-Supervised Semantic Segmentation in ECG Delineation Isp ecg delineation dataset, 2024
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T14:37:29.581567Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 6d67499b-84c0-4232-b03e-a0ec815b2fcc · outbound
This paper cites Ecgvednet: A variational encoder-decoder network for ecg delineation in morphology variant ecgs.
SemiSegECG: A Multi-Dataset Benchmark for Semi-Supervised Semantic Segmentation in ECG Delineation Ecgvednet: A variational encoder-decoder network for ecg delineation in morphology variant ecgs
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T14:37:29.549538Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation b1fbb4f6-5078-431d-9e78-09a010fe40aa · outbound
This paper cites Deeplab: Semantic image segmentation with deep convolutional nets, atrous convolu- tion, and fully connected crfs.
SemiSegECG: A Multi-Dataset Benchmark for Semi-Supervised Semantic Segmentation in ECG Delineation Deeplab: Semantic image segmentation with deep convolutional nets, atrous convolu- tion, and fully connected crfs
Reference 3
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8b9e817f-a209-4697-b2ab-b0a49955ca1d · outbound
This paper cites Semi-supervised semantic segmentation with cross pseudo supervision.
SemiSegECG: A Multi-Dataset Benchmark for Semi-Supervised Semantic Segmentation in ECG Delineation Semi-supervised semantic segmentation with cross pseudo supervision
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T14:37:29.497447Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation e62e9d1c-cb1e-4dea-82d7-e08a1c0c6dcb · outbound
This paper cites Post-processing refined ecg de- lineation based on 1d-unet.
SemiSegECG: A Multi-Dataset Benchmark for Semi-Supervised Semantic Segmentation in ECG Delineation Post-processing refined ecg de- lineation based on 1d-unet
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T14:37:29.463333Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 04620a09-7154-4077-8979-1237d0d53c57 · outbound
This paper cites Randaugment: Practical automated data augmen- tation with a reduced search space.
SemiSegECG: A Multi-Dataset Benchmark for Semi-Supervised Semantic Segmentation in ECG Delineation Randaugment: Practical automated data augmen- tation with a reduced search space
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T14:37:29.429731Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation f212b037-b398-4d29-ab7b-53e15939cb4a · outbound
This paper cites An image is worth 16x16 words: Transformers for image recognition at scale.
SemiSegECG: A Multi-Dataset Benchmark for Semi-Supervised Semantic Segmentation in ECG Delineation An image is worth 16x16 words: Transformers for image recognition at scale
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T14:37:29.402169Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation a759f83e-e220-472c-8ff8-90f6f03cc01e · outbound
This paper cites Revisiting qrs detection methodologies for portable, wearable, battery-operated, and wireless ecg sys- tems.
SemiSegECG: A Multi-Dataset Benchmark for Semi-Supervised Semantic Segmentation in ECG Delineation Revisiting qrs detection methodologies for portable, wearable, battery-operated, and wireless ecg sys- tems
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T14:37:29.366082Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation c5aa5efb-18e1-4593-9e08-853ac22d01c2 · outbound
This paper cites ECG signal processing, classification and interpretation: a comprehensive frame- work of computational intelligence.
SemiSegECG: A Multi-Dataset Benchmark for Semi-Supervised Semantic Segmentation in ECG Delineation ECG signal processing, classification and interpretation: a comprehensive frame- work of computational intelligence
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T14:37:29.333884Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation d46c6130-00b7-4118-8987-a0a14853ef2c · outbound
This paper cites Physiobank, physiotoolkit, and physionet: compo- nents of a new research resource for complex physiologic signals.
SemiSegECG: A Multi-Dataset Benchmark for Semi-Supervised Semantic Segmentation in ECG Delineation Physiobank, physiotoolkit, and physionet: compo- nents of a new research resource for complex physiologic signals
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T14:37:29.305514Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation d718b51c-49b0-40f2-acd3-59bde7c9b76e · outbound
This paper cites Deep residual learning for image recognition.
SemiSegECG: A Multi-Dataset Benchmark for Semi-Supervised Semantic Segmentation in ECG Delineation Deep residual learning for image recognition
Reference 11
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T14:37:27.627285Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1a4705b8-8afd-469d-ae35-3bca8b866142 · outbound
This paper cites U-net architecture for the automatic detection and de- lineation of the electrocardiogram.
SemiSegECG: A Multi-Dataset Benchmark for Semi-Supervised Semantic Segmentation in ECG Delineation U-net architecture for the automatic detection and de- lineation of the electrocardiogram
Reference 12
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T14:37:29.247842Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation cea16882-d771-4d9f-a4da-16307ef462dc · outbound
This paper cites Delineation of the electrocardiogram with a mixed- quality-annotations dataset using convolutional neural net- works.
SemiSegECG: A Multi-Dataset Benchmark for Semi-Supervised Semantic Segmentation in ECG Delineation Delineation of the electrocardiogram with a mixed- quality-annotations dataset using convolutional neural net- works
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T14:37:29.222779Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 3007d15e-01e6-472b-b0c4-91c34a8611f7 · outbound
This paper cites Generalising electrocardiogram detec- tion and delineation: training convolutional neural networks with synthetic data augmentation.
SemiSegECG: A Multi-Dataset Benchmark for Semi-Supervised Semantic Segmentation in ECG Delineation Generalising electrocardiogram detec- tion and delineation: training convolutional neural networks with synthetic data augmentation
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T14:37:29.179548Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 187b88bf-5973-4086-8b7e-62999ac8489d · outbound
This paper cites Deep learning based ecg segmentation for delineation of diverse arrhyth- mias.
SemiSegECG: A Multi-Dataset Benchmark for Semi-Supervised Semantic Segmentation in ECG Delineation Deep learning based ecg segmentation for delineation of diverse arrhyth- mias
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T14:37:29.155243Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 6dcbbef9-200e-4016-8017-840afee3a4fc · outbound
This paper cites Ludb: a new open-access validation tool for electrocar- diogram delineation algorithms.
SemiSegECG: A Multi-Dataset Benchmark for Semi-Supervised Semantic Segmentation in ECG Delineation Ludb: a new open-access validation tool for electrocar- diogram delineation algorithms
Reference 16
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T14:37:29.119158Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 6cdceb06-213c-4714-8841-66e2ab675313 · outbound
This paper cites Imagenet classification with deep convolutional neural net- works.
SemiSegECG: A Multi-Dataset Benchmark for Semi-Supervised Semantic Segmentation in ECG Delineation Imagenet classification with deep convolutional neural net- works
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T14:37:29.093736Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation a688740e-70e2-4e5d-9a76-c83d8b64edb4 · outbound
This paper cites A database for evaluation of algorithms for mea- surement of qt and other waveform intervals in the ecg.
SemiSegECG: A Multi-Dataset Benchmark for Semi-Supervised Semantic Segmentation in ECG Delineation A database for evaluation of algorithms for mea- surement of qt and other waveform intervals in the ecg
Reference 18
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T14:37:29.071400Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 74008ec0-5ba2-4880-9d08-442075167e78 · outbound
This paper cites Efficient data augmentation policy for electrocardiograms.
SemiSegECG: A Multi-Dataset Benchmark for Semi-Supervised Semantic Segmentation in ECG Delineation Efficient data augmentation policy for electrocardiograms
Reference 19
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T14:37:29.050149Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation d18cb9bf-8481-4f44-95ca-252d56748d2b · outbound
This paper cites Ecg segnet: An ecg delineation model based on the encoder-decoder structure.
SemiSegECG: A Multi-Dataset Benchmark for Semi-Supervised Semantic Segmentation in ECG Delineation Ecg segnet: An ecg delineation model based on the encoder-decoder structure
Reference 20
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T14:37:29.020754Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation b4340325-ceff-417b-ab81-5e4ead9a9e73 · outbound
This paper cites Specialized ecg data augmentation method: leveraging precordial lead positional variability.
SemiSegECG: A Multi-Dataset Benchmark for Semi-Supervised Semantic Segmentation in ECG Delineation Specialized ecg data augmentation method: leveraging precordial lead positional variability
Reference 21
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T14:37:28.992325Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation d9814ac7-9928-4025-a5a1-0a38f8da8f81 · outbound
This paper cites Performance analy- sis of ten common qrs detectors on different ecg application cases.
SemiSegECG: A Multi-Dataset Benchmark for Semi-Supervised Semantic Segmentation in ECG Delineation Performance analy- sis of ten common qrs detectors on different ecg application cases
Reference 22
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T14:37:28.968720Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 949776be-5e69-4247-85f0-df194309f27d · outbound
This paper cites Bootstrapping semantic segmentation with re- gional contrast.
SemiSegECG: A Multi-Dataset Benchmark for Semi-Supervised Semantic Segmentation in ECG Delineation Bootstrapping semantic segmentation with re- gional contrast
Reference 23
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T14:37:28.930208Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 2dd8c9ae-9284-4072-a944-5202b0133fdd · outbound
This paper cites Fully convolutional networks for semantic segmentation.
SemiSegECG: A Multi-Dataset Benchmark for Semi-Supervised Semantic Segmentation in ECG Delineation Fully convolutional networks for semantic segmentation
Reference 24
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T14:37:28.902576Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 684e3cc6-088f-420b-9adf-313632ba6f65 · outbound
This paper cites SGDR: Stochastic gradi- ent descent with warm restarts.
SemiSegECG: A Multi-Dataset Benchmark for Semi-Supervised Semantic Segmentation in ECG Delineation SGDR: Stochastic gradi- ent descent with warm restarts
Reference 25
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T14:37:28.872457Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation a982e391-f07c-4333-bfd8-70c41d6fb43c · outbound
This paper cites Decoupled weight de- cay regularization.
SemiSegECG: A Multi-Dataset Benchmark for Semi-Supervised Semantic Segmentation in ECG Delineation Decoupled weight de- cay regularization
Reference 26
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T14:37:28.840937Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 35343052-eb77-46a5-80c2-889aabcbdd04 · outbound
This paper cites A wavelet-based ecg delineator: evaluation on standard databases.
SemiSegECG: A Multi-Dataset Benchmark for Semi-Supervised Semantic Segmentation in ECG Delineation A wavelet-based ecg delineator: evaluation on standard databases
Reference 27
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T14:37:28.791029Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation b0b13ff5-179d-4d86-83f6-71c89f497414 · outbound
This paper cites Guiding masked representation learning to capture spatio- temporal relationship of electrocardiogram.
SemiSegECG: A Multi-Dataset Benchmark for Semi-Supervised Semantic Segmentation in ECG Delineation Guiding masked representation learning to capture spatio- temporal relationship of electrocardiogram
Reference 28
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T14:37:28.758033Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation e014f2c1-3b9a-4b95-8f30-af7fd0a8ad3f · outbound
This paper cites Data Augmentation for Electrocardiogram Classification with Deep Neural Network.
SemiSegECG: A Multi-Dataset Benchmark for Semi-Supervised Semantic Segmentation in ECG Delineation Data Augmentation for Electrocardiogram Classification with Deep Neural Network
Reference 29
- Resolution
- verified exact
- local_arxiv, observed 2026-08-06T14:37:28.252014Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 9b375efd-8ea1-4838-a3a4-1a127c0954a7 · outbound
This paper cites A Survey on Semi-Supervised Semantic Segmentation.
SemiSegECG: A Multi-Dataset Benchmark for Semi-Supervised Semantic Segmentation in ECG Delineation A Survey on Semi-Supervised Semantic Segmentation
Reference 30
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T14:37:27.945603Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 90d34179-dd9b-4f0a-834f-850a7f90754d · outbound
This paper cites A systematic survey of data augmentation of ecg signals for ai applications.
SemiSegECG: A Multi-Dataset Benchmark for Semi-Supervised Semantic Segmentation in ECG Delineation A systematic survey of data augmentation of ecg signals for ai applications
Reference 31
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T14:37:28.729520Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 35ba9db6-fc2d-458a-abd2-a04927ecb7f5 · outbound
This paper cites Automatic diagnosis of the 12-lead ecg using a deep neural network.Nature commu- nications, 11(1):1760, 2020.
SemiSegECG: A Multi-Dataset Benchmark for Semi-Supervised Semantic Segmentation in ECG Delineation Automatic diagnosis of the 12-lead ecg using a deep neural network.Nature commu- nications, 11(1):1760, 2020
Reference 32
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T14:37:28.704183Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation ef0ca254-0841-4f15-985d-e69c7d3c3a8e · outbound
This paper cites Multiple electrocardiogram generator with single-lead electrocardiogram.
SemiSegECG: A Multi-Dataset Benchmark for Semi-Supervised Semantic Segmentation in ECG Delineation Multiple electrocardiogram generator with single-lead electrocardiogram
Reference 33
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T14:37:28.668166Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation b37e8331-8130-4354-8b78-0112fdc4a6f9 · outbound
This paper cites Fixmatch: Simplifying semi-supervised learning with consistency and confidence.
SemiSegECG: A Multi-Dataset Benchmark for Semi-Supervised Semantic Segmentation in ECG Delineation Fixmatch: Simplifying semi-supervised learning with consistency and confidence
Reference 34
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T14:37:28.021746Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7b57bc04-d483-4ecf-b3cb-b2b9e8df2769 · outbound
This paper cites Dropout: a simple way to prevent neural networks from overfitting.
SemiSegECG: A Multi-Dataset Benchmark for Semi-Supervised Semantic Segmentation in ECG Delineation Dropout: a simple way to prevent neural networks from overfitting
Reference 35
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T14:37:28.619447Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 40928352-5d63-409a-85c8-0ede33e6e53e · outbound
This paper cites Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results.
SemiSegECG: A Multi-Dataset Benchmark for Semi-Supervised Semantic Segmentation in ECG Delineation Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results
Reference 36
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T14:37:28.565448Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 192ca11f-1770-4feb-8736-21dc23ef8889 · outbound
This paper cites Training data-efficient image transformers & distillation through at- tention.
SemiSegECG: A Multi-Dataset Benchmark for Semi-Supervised Semantic Segmentation in ECG Delineation Training data-efficient image transformers & distillation through at- tention
Reference 37
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T14:37:28.534154Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation d24cb01c-3618-422f-b6ab-c8c4fec11292 · outbound
This paper cites Normal values of corrected heart- rate variability in 10-second electrocardiograms for all ages.
SemiSegECG: A Multi-Dataset Benchmark for Semi-Supervised Semantic Segmentation in ECG Delineation Normal values of corrected heart- rate variability in 10-second electrocardiograms for all ages
Reference 38
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T14:37:28.496707Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation e892ff12-ccc5-4a86-8983-13412455f7b5 · outbound
This paper cites Attention is all you need.
SemiSegECG: A Multi-Dataset Benchmark for Semi-Supervised Semantic Segmentation in ECG Delineation Attention is all you need
Reference 39
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T14:37:28.063763Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3658ee46-f225-4212-9e38-00df8b02aeae · outbound
This paper cites Ptb-xl, a large publicly available electrocardiog- raphy dataset.
SemiSegECG: A Multi-Dataset Benchmark for Semi-Supervised Semantic Segmentation in ECG Delineation Ptb-xl, a large publicly available electrocardiog- raphy dataset
Reference 40
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T14:37:28.408414Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation c8c7e574-74c6-476b-9323-3b669daafa9c · outbound
This paper cites St++: Make self-training work better for semi-supervised se- mantic segmentation.
SemiSegECG: A Multi-Dataset Benchmark for Semi-Supervised Semantic Segmentation in ECG Delineation St++: Make self-training work better for semi-supervised se- mantic segmentation
Reference 41
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T14:37:28.366682Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation eacc4921-5ca1-46f2-8ee7-490fc89f8d54 · outbound
This paper cites Augmentation matters: A simple-yet- effective approach to semi-supervised semantic segmenta- tion.
SemiSegECG: A Multi-Dataset Benchmark for Semi-Supervised Semantic Segmentation in ECG Delineation Augmentation matters: A simple-yet- effective approach to semi-supervised semantic segmenta- tion
Reference 42
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T14:37:28.329320Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 55b7407a-0397-481a-a62f-2cd80f4b8d49 · outbound
This paper cites A 12-lead ecg database to identify ori- gins of idiopathic ventricular arrhythmia containing 334 pa- tients.
SemiSegECG: A Multi-Dataset Benchmark for Semi-Supervised Semantic Segmentation in ECG Delineation A 12-lead ecg database to identify ori- gins of idiopathic ventricular arrhythmia containing 334 pa- tients
Reference 43
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T14:37:28.302609Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation c88648a3-4654-4193-aea2-19a56dc30705 · outbound
This paper cites Rethinking semantic segmen- tation from a sequence-to-sequence perspective with trans- formers.
SemiSegECG: A Multi-Dataset Benchmark for Semi-Supervised Semantic Segmentation in ECG Delineation Rethinking semantic segmen- tation from a sequence-to-sequence perspective with trans- formers
Reference 44
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T14:37:28.123398Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Pith citing papers
No inbound Pith citation observations are available.