Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Contour-enhanced attention CNN for CT-based COVID-19 segmentation
R. Karthik, R. Menaka, M. Hariharan, et al.
Pattern Recognition (2022) Vol. 125, pp. 108538-108538
Open Access | Times Cited: 48

Showing 1-25 of 48 citing articles:

Haar wavelet downsampling: A simple but effective downsampling module for semantic segmentation
Guoping Xu, Wentao Liao, Xuan Zhang, et al.
Pattern Recognition (2023) Vol. 143, pp. 109819-109819
Closed Access | Times Cited: 55
Automated detection and forecasting of COVID-19 using deep learning techniques: A review
Afshin Shoeibi, Marjane Khodatars, Mahboobeh Jafari, et al.
Neurocomputing (2024) Vol. 577, pp. 127317-127317
Open Access | Times Cited: 46
SAN-Net: Learning generalization to unseen sites for stroke lesion segmentation with self-adaptive normalization
Weiyi Yu, Zhizhong Huang, Junping Zhang, et al.
Computers in Biology and Medicine (2023) Vol. 156, pp. 106717-106717
Open Access | Times Cited: 19
Attention guided tongue segmentation with geometric knowledge in complex environments
Zonghai Huang, Rui Huang, Jingting Zhang, et al.
Biomedical Signal Processing and Control (2025) Vol. 104, pp. 107426-107426
Closed Access
Unlocking the Power of 3D Convolutional Neural Networks for COVID-19 Detection: A Comprehensive Review
Ademola E. Ilesanmi, Taiwo Ilesanmi, Babatunde O. Ajayi, et al.
Deleted Journal (2025)
Closed Access
Memory-Guided Transformer with group attention for knee MRI diagnosis
Rui Huang, Zonghai Huang, Hao Zhou, et al.
Pattern Recognition (2025), pp. 111417-111417
Closed Access
A deep cross-modal neural cognitive diagnosis framework for modeling student performance
Lingyun Song, Mengting He, Xuequn Shang, et al.
Expert Systems with Applications (2023) Vol. 230, pp. 120675-120675
Closed Access | Times Cited: 14
Advances in attention mechanisms for medical image segmentation
Jianpeng Zhang, Xiaomin Chen, Bing Yang, et al.
Computer Science Review (2025) Vol. 56, pp. 100721-100721
Closed Access
Combining edge guidance and feature pyramid for medical image segmentation
Shao‐Long Chen, Changzhen Qiu, W. X. Yang, et al.
Biomedical Signal Processing and Control (2022) Vol. 78, pp. 103960-103960
Closed Access | Times Cited: 21
A teacher–student framework with Fourier Transform augmentation for COVID-19 infection segmentation in CT images
Han Chen, Yifan Jiang, Hanseok Ko, et al.
Biomedical Signal Processing and Control (2022) Vol. 79, pp. 104250-104250
Open Access | Times Cited: 20
A modified DeepLabV3+ based semantic segmentation of chest computed tomography images for COVID‐19 lung infections
Hasan Polat
International Journal of Imaging Systems and Technology (2022) Vol. 32, Iss. 5, pp. 1481-1495
Open Access | Times Cited: 19
Momentum contrast transformer for COVID-19 diagnosis with knowledge distillation
Aimei Dong, Jian Liu, Guodong Zhang, et al.
Pattern Recognition (2023) Vol. 143, pp. 109732-109732
Open Access | Times Cited: 11
Performance Analysis of Machine Learning and Deep Learning Models for Classification of Alzheimer’s Disease from Brain MRI
T. Illakiya, R. Karthik
Traitement du signal (2022) Vol. 39, Iss. 6, pp. 1961-1970
Open Access | Times Cited: 18
CT-based severity assessment for COVID-19 using weakly supervised non-local CNN
R. Karthik, R. Menaka, M. Hariharan, et al.
Applied Soft Computing (2022) Vol. 121, pp. 108765-108765
Open Access | Times Cited: 16
An effective U-net model for diagnosing Covid-19 infection
Shirin Kordnoori, Malihe Sabeti, Hamidreza Mostafaei, et al.
Intelligence-Based Medicine (2024) Vol. 10, pp. 100156-100156
Open Access | Times Cited: 2
Cardiac segmentation on CT Images through shape-aware contour attentions
Sanguk Park, Minyoung Chung
Computers in Biology and Medicine (2022) Vol. 147, pp. 105782-105782
Open Access | Times Cited: 12
Data-attention-YOLO (DAY): A comprehensive framework for mesoscale eddy identification
Xinning Wang, Xuegong Wang, Chong Li, et al.
Pattern Recognition (2022) Vol. 131, pp. 108870-108870
Closed Access | Times Cited: 12
An efficient deep multi‐task learning structure for covid‐19 disease
Shirin Kordnoori, Malihe Sabeti, Hamidreza Mostafaei, et al.
IET Image Processing (2023) Vol. 17, Iss. 13, pp. 3728-3745
Open Access | Times Cited: 6
A Review of Deep Learning Imaging Diagnostic Methods for COVID-19
Tao Zhou, Fengzhen Liu, Huiling Lu, et al.
Electronics (2023) Vol. 12, Iss. 5, pp. 1167-1167
Open Access | Times Cited: 5
Weakly supervised segmentation of COVID-19 infection with local lesion coherence on CT images
Wanchun Sun, Xin Feng, Jingyao Liu, et al.
Biomedical Signal Processing and Control (2022) Vol. 79, pp. 104099-104099
Open Access | Times Cited: 9
ThumbDet: One thumbnail image is enough for object detection
Yongqiang Zhang, Yin Zhang, Rui Tian, et al.
Pattern Recognition (2023) Vol. 138, pp. 109424-109424
Closed Access | Times Cited: 4
SAA-UNet: Spatial Attention and Attention Gate UNet for COVID-19 Pneumonia Segmentation from Computed Tomography
Shroog Alshomrani, Muhammad Arif, Mohammed A. Al Ghamdi
Diagnostics (2023) Vol. 13, Iss. 9, pp. 1658-1658
Open Access | Times Cited: 4
CGS‐Net: A classification‐guided framework for automated infection segmentation of COVID‐19 from CT images
Wen Zhou, Jihong Wang, Yuhang Wang, et al.
International Journal of Imaging Systems and Technology (2024) Vol. 34, Iss. 1
Closed Access | Times Cited: 1
U-TranSvision: Transformer-based deep supervision approach for COVID-19 lesion segmentation on Computed Tomography images
Mahmut AĞRALI, Volkan Kılıç
Biomedical Signal Processing and Control (2024) Vol. 93, pp. 106167-106167
Closed Access | Times Cited: 1
DLF-Sul: a multi-module deep learning framework for prediction of S-sulfinylation sites in proteins
Ning Qiao, Jinmou Li
Briefings in Bioinformatics (2022) Vol. 23, Iss. 5
Closed Access | Times Cited: 6
Page 1 - Next Page

Scroll to top