ResearchTrend.AI
  • Communities
  • Connect sessions
  • AI calendar
  • Organizations
  • Join Slack
  • Contact Sales
Papers
Communities
Social Events
Terms and Conditions
Pricing
Contact Sales
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2026 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2001.04689
  4. Cited By
Deep Learning for ECG Segmentation

Deep Learning for ECG Segmentation

Studies in Computational Intelligence (SCI), 2019
14 January 2020
V. Moskalenko
N. Zolotykh
Grigory V. Osipov
ArXiv (abs)PDFHTML

Papers citing "Deep Learning for ECG Segmentation"

13 / 13 papers shown
anyECG-chat: A Generalist ECG-MLLM for Flexible ECG Input and Multi-Task Understanding
anyECG-chat: A Generalist ECG-MLLM for Flexible ECG Input and Multi-Task Understanding
Haitao Li
Ziyu Li
Yiheng Mao
Ziyi Liu
Zhoujian Sun
Zhengxing Huang
190
3
0
01 Jun 2025
Learning General Representation of 12-Lead Electrocardiogram with a
  Joint-Embedding Predictive Architecture
Learning General Representation of 12-Lead Electrocardiogram with a Joint-Embedding Predictive Architecture
Sehun Kim
289
8
0
11 Oct 2024
Self-Trained Model for ECG Complex Delineation
Self-Trained Model for ECG Complex Delineation
A. Avetisyan
Nikolas Khachaturov
A. Asatryan
Shahane Tigranyan
Yury Markin
148
1
0
04 Jun 2024
Anatomical Region Recognition and Real-time Bone Tracking Methods by
  Dynamically Decoding A-Mode Ultrasound Signals
Anatomical Region Recognition and Real-time Bone Tracking Methods by Dynamically Decoding A-Mode Ultrasound Signals
Bangyu Lan
Stefano Stramigioli
Kenan Niu
225
2
0
29 May 2024
Deep Learning based acoustic measurement approach for robotic
  applications on orthopedics
Deep Learning based acoustic measurement approach for robotic applications on orthopedicsIEEE International Conference on Robotics and Automation (ICRA), 2024
Bangyu Lan
M. Abayazid
Nico Verdonschot
Stefano Stramigioli
Kenan Niu
130
4
0
09 Mar 2024
A Comprehensive Survey on Applications of Transformers for Deep Learning
  Tasks
A Comprehensive Survey on Applications of Transformers for Deep Learning TasksExpert systems with applications (ESWA), 2023
Saidul Islam
Hanae Elmekki
Ahmed Elsebai
Jamal Bentahar
Najat Drawel
Gaith Rjoub
Witold Pedrycz
ViTMedIm
273
409
0
11 Jun 2023
Deep learning based ECG segmentation for delineation of diverse
  arrhythmias
Deep learning based ECG segmentation for delineation of diverse arrhythmiasPLoS ONE (PLoS ONE), 2023
Chankyu Joung
Mijin Kim
Taejin Paik
S. Kong
Seung-Young Oh
...
Joong-Sik Hong
Wan-Joong Kim
Woong Kook
M. Cha
Otto van Koert
216
15
0
13 Apr 2023
Investigating Deep Learning Benchmarks for Electrocardiography Signal
  Processing
Investigating Deep Learning Benchmarks for Electrocardiography Signal Processing
Hao Wen
Ji-Su Kang
87
5
0
09 Apr 2022
A Deep Bayesian Neural Network for Cardiac Arrhythmia Classification
  with Rejection from ECG Recordings
A Deep Bayesian Neural Network for Cardiac Arrhythmia Classification with Rejection from ECG Recordings
Wen-Rang Zhang
Xinxin Di
Guodong Wei
Shijia Geng
Zhaoji Fu
linda Qiao
UQCVBDL
97
2
0
26 Feb 2022
Generalizing electrocardiogram delineation -- Training convolutional
  neural networks with synthetic data augmentation
Generalizing electrocardiogram delineation -- Training convolutional neural networks with synthetic data augmentation
Guillermo Jiménez-Pérez
J. Acosta
A. Alcaine
Oscar Camara
242
8
0
25 Nov 2021
Problems of representation of electrocardiograms in convolutional neural
  networks
Problems of representation of electrocardiograms in convolutional neural networksIEEE International Joint Conference on Neural Network (IJCNN), 2020
Iana Sereda
Sergey Alekseev
A. Koneva
Alexey Khorkin
Grigory V. Osipov
186
1
0
01 Dec 2020
Electrocardiogram Generation and Feature Extraction Using a Variational
  Autoencoder
Electrocardiogram Generation and Feature Extraction Using a Variational Autoencoder
V. Kuznetsov
V. Moskalenko
N. Zolotykh
DRL
129
25
0
01 Feb 2020
Opportunities and Challenges of Deep Learning Methods for
  Electrocardiogram Data: A Systematic Review
Opportunities and Challenges of Deep Learning Methods for Electrocardiogram Data: A Systematic Review
linda Qiao
Yuxi Zhou
Junyuan Shang
Cao Xiao
Jimeng Sun
413
163
0
28 Dec 2019
1
Page 1 of 1