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OpenAlex Citation Counts

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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:

Skin lesion segmentation using fully convolutional networks: A comparative experimental study
Ruya Kaymak, Çağrı Kaymak, Ayşegül Uçar
Expert Systems with Applications (2020) Vol. 161, pp. 113742-113742
Closed Access | Times Cited: 71

Showing 1-25 of 71 citing articles:

Medical image segmentation using deep semantic-based methods: A review of techniques, applications and emerging trends
Imran Qureshi, Junhua Yan, Qaisar Abbas, et al.
Information Fusion (2022) Vol. 90, pp. 316-352
Closed Access | Times Cited: 146
A survey, review, and future trends of skin lesion segmentation and classification
Md. Kamrul Hasan, Md. Asif Ahamad, Choon Hwai Yap, et al.
Computers in Biology and Medicine (2023) Vol. 155, pp. 106624-106624
Open Access | Times Cited: 86
A survey on deep learning for skin lesion segmentation
Zahra Mirikharaji, Kumar Abhishek, Alceu Bissoto, et al.
Medical Image Analysis (2023) Vol. 88, pp. 102863-102863
Open Access | Times Cited: 81
New Trends in Melanoma Detection Using Neural Networks: A Systematic Review
Dan Popescu, Mohamed El-Khatib, Hassan El-Khatib, et al.
Sensors (2022) Vol. 22, Iss. 2, pp. 496-496
Open Access | Times Cited: 77
A novel SpaSA based hyper-parameter optimized FCEDN with adaptive CNN classification for skin cancer detection
Rizwan Ali, A. Manikandan, Rui Lei, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 28
Advances in Medical Image Segmentation: A Comprehensive Review of Traditional, Deep Learning and Hybrid Approaches
Yan Xu, Rixiang Quan, Weiting Xu, et al.
Bioengineering (2024) Vol. 11, Iss. 10, pp. 1034-1034
Open Access | Times Cited: 19
W-net and inception residual network for skin lesion segmentation and classification
Khouloud Sahib, Ahlem Melouah, Fadel Touré, et al.
Applied Intelligence (2021) Vol. 52, Iss. 4, pp. 3976-3994
Closed Access | Times Cited: 71
Skin Lesion Extraction Using Multiscale Morphological Local Variance Reconstruction Based Watershed Transform and Fast Fuzzy C-Means Clustering
Ranjita Rout, Priyadarsan Parida, Youseef Alotaibi, et al.
Symmetry (2021) Vol. 13, Iss. 11, pp. 2085-2085
Open Access | Times Cited: 63
Wavelet transform based deep residual neural network and ReLU based Extreme Learning Machine for skin lesion classification
Fayadh Alenezi, Ammar Armghan, Kemal Polat
Expert Systems with Applications (2022) Vol. 213, pp. 119064-119064
Closed Access | Times Cited: 62
Skin cancer image segmentation utilizing a novel EN-GWO based hyper-parameter optimized FCEDN
Rasmiranjan Mohakud, Rajashree Dash
Journal of King Saud University - Computer and Information Sciences (2022) Vol. 34, Iss. 10, pp. 9889-9904
Open Access | Times Cited: 53
DeepLabv3+-Based Segmentation and Best Features Selection Using Slime Mould Algorithm for Multi-Class Skin Lesion Classification
Mehwish Zafar, Javeria Amin, Muhammad Sharif, et al.
Mathematics (2023) Vol. 11, Iss. 2, pp. 364-364
Open Access | Times Cited: 30
Segmentation and classification of skin lesions using hybrid deep learning method in the Internet of Medical Things
Arslan Akram, Javed Rashid, M. Arfan Jaffar, et al.
Skin Research and Technology (2023) Vol. 29, Iss. 11
Open Access | Times Cited: 29
Deep Learning and Optimization-Based Methods for Skin Lesions Segmentation: A Review
Khalid M. Hosny, Doaa Elshoura, Ehab R. Mohamed, et al.
IEEE Access (2023) Vol. 11, pp. 85467-85488
Open Access | Times Cited: 27
A Novel Multi-Task Learning Network Based on Melanoma Segmentation and Classification with Skin Lesion Images
Fayadh Alenezi, Ammar Armghan, Kemal Polat
Diagnostics (2023) Vol. 13, Iss. 2, pp. 262-262
Open Access | Times Cited: 25
Skin Cancer Detection and Classification Using Neural Network Algorithms: A Systematic Review
Pamela Hermosilla, Ricardo Soto, Emanuel Vega, et al.
Diagnostics (2024) Vol. 14, Iss. 4, pp. 454-454
Open Access | Times Cited: 9
Lite-MixedNet:Lightweight and efficient hybrid network for medical image segmentation
Zitong Ren, Yongming Li, Liejun Wang, et al.
Pattern Recognition (2025), pp. 111378-111378
Closed Access | Times Cited: 1
A multi-stage melanoma recognition framework with deep residual neural network and hyperparameter optimization-based decision support in dermoscopy images
Fayadh Alenezi, Ammar Armghan, Kemal Polat
Expert Systems with Applications (2022) Vol. 215, pp. 119352-119352
Closed Access | Times Cited: 31
DTP-Net: A convolutional neural network model to predict threshold for localizing the lesions on dermatological macro-images
Vipin Venugopal, Justin Joseph, Moumita Das, et al.
Computers in Biology and Medicine (2022) Vol. 148, pp. 105852-105852
Closed Access | Times Cited: 30
Development of a compressed FCN architecture for semantic segmentation using Particle Swarm Optimization
Mohit Agarwal, Suneet Kumar Gupta, Kanad K. Biswas
Neural Computing and Applications (2023) Vol. 35, Iss. 16, pp. 11833-11846
Open Access | Times Cited: 18
A deep learning-based illumination transform for devignetting photographs of dermatological lesions
Vipin Venugopal, Malaya Kumar Nath, Justin Joseph, et al.
Image and Vision Computing (2024) Vol. 142, pp. 104909-104909
Closed Access | Times Cited: 6
A Reinforcement Learning Algorithm for Automated Detection of Skin Lesions
Usman Ahmad Usmani, Junzo Watada, Jafreezal Jaafar, et al.
Applied Sciences (2021) Vol. 11, Iss. 20, pp. 9367-9367
Open Access | Times Cited: 33
CGFFCM: A color image segmentation method based on cluster-weight and feature-weight learning
Amin Golzari Oskouei, Mahdi Hashemzadeh
Software Impacts (2022) Vol. 11, pp. 100228-100228
Closed Access | Times Cited: 28
Federated and Transfer Learning Methods for the Classification of Melanoma and Nonmelanoma Skin Cancers: A Prospective Study
Shafia Riaz, Ahmad Naeem, Hassaan Malik, et al.
Sensors (2023) Vol. 23, Iss. 20, pp. 8457-8457
Open Access | Times Cited: 16
Artificial intelligence-assisted detection model for melanoma diagnosis using deep learning techniques
Hediye Orhan, Emrehan Yavşan
Mathematical Modelling and Numerical Simulation with Applications (2023) Vol. 3, Iss. 2, pp. 159-169
Open Access | Times Cited: 14
Recent Advances in Diagnosis of Skin Lesions Using Dermoscopic Images Based on Deep Learning
Yali Nie, Paolo Sommella, Marco Carratù, et al.
IEEE Access (2022) Vol. 10, pp. 95716-95747
Open Access | Times Cited: 20
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