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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:

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

Showing 25 citing articles:

SkinNet-INIO: Multiclass Skin Lesion Localization and Classification Using Fusion-Assisted Deep Neural Networks and Improved Nature-Inspired Optimization Algorithm
Muneezah Hussain, Muhammad Attique Khan, Robertas Damaševičius, et al.
Diagnostics (2023) Vol. 13, Iss. 18, pp. 2869-2869
Open Access | Times Cited: 34
Fuzzy Logic with Deep Learning for Detection of Skin Cancer
Sumit Kumar Singh, Vahid Abolghasemi, Mohammad Hossein Anisi
Applied Sciences (2023) Vol. 13, Iss. 15, pp. 8927-8927
Open Access | Times Cited: 29
Optimization Convolutional Neural Network for Automatic Skin Lesion Diagnosis Using a Genetic Algorithm
Omran Salih, Kevin J. Duffy
Applied Sciences (2023) Vol. 13, Iss. 5, pp. 3248-3248
Open Access | Times Cited: 25
FDUM-Net: An enhanced FPN and U-Net architecture for skin lesion segmentation
H. Sharen, Malathy Jawahar, L. Jani Anbarasi, et al.
Biomedical Signal Processing and Control (2024) Vol. 91, pp. 106037-106037
Closed Access | Times Cited: 9
Systematic review of approaches to detection and classification of skin cancer using artificial intelligence: Development and prospects
Ulyana A. Lyakhova, Pavel Lyakhov
Computers in Biology and Medicine (2024) Vol. 178, pp. 108742-108742
Closed Access | Times Cited: 6
Classification of skin cancer from dermatological image by multimodal method
Tinghao Zhang, Yinglong Wang, Dezheng Wang, et al.
(2025), pp. 33-33
Closed Access
Precision and efficiency in skin cancer segmentation through a dual encoder deep learning model
Ahmed A. A. Gad-Elrab, Guangmin Sun, Anas Bilal, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access
Melanoma lesion localization using UNet and explainable AI
Hareem Kibriya, Ayesha Siddiqa, Wazir Zada Khan
Neural Computing and Applications (2025)
Closed Access
Pixel-guided pattern alignment based Hopfield Neural Networks for generalize cancer diagnosis
Fayadh Alenezi, Şaban Öztürk
Biomedical Signal Processing and Control (2025) Vol. 103, pp. 107397-107397
Closed Access
SL-R-CNN-HHO: multi-class skin lesion classification using region-based convolutional neural networks and harris hawk optimization on the HAM dataset
Mahendra Prasad Sharma, Laveena Sehgal
International Journal of Information Technology (2025)
Closed Access
Artificial Intelligence based real-time automatic detection and classification of skin lesion in dermoscopic samples using DenseNet-169 architecture
A. Ashwini, Purushothaman Kailasnath, A. Rosi, et al.
Journal of Intelligent & Fuzzy Systems (2023) Vol. 45, Iss. 4, pp. 6943-6958
Closed Access | Times Cited: 9
Impact of optimizers functions on detection of Melanoma using transfer learning architectures
Serhat Kılıçarslan, Hatice Aktaş Aydın, Kemal Adem, et al.
Multimedia Tools and Applications (2024)
Open Access | Times Cited: 2
Melanoma detection: integrating dilated convolutional methods with mutual learning-based artificial bee colony and reinforcement learning
Fengyu Hu, Jiayuan Zhang
Multiscale and Multidisciplinary Modeling Experiments and Design (2024) Vol. 8, Iss. 1
Closed Access | Times Cited: 2
Systematic Review of Deep Learning Techniques in Skin Cancer Detection
Carolina Magalhaes, Joaquim Mendes, Ricardo Vardasca
BioMedInformatics (2024) Vol. 4, Iss. 4, pp. 2251-2270
Open Access | Times Cited: 2
Skin Melanoma Detection Using Image Augmentation
D. Sivabalaselvamani, K. Nanthini, D. Selvakarthi, et al.
(2023), pp. 1624-1630
Closed Access | Times Cited: 4
Melanoma classification using generative adversarial network and proximal policy optimization
Xiangui Ju, Chi‐Ho Lin, Suan Lee, et al.
Photochemistry and Photobiology (2024)
Closed Access | Times Cited: 1
Segmentation and Classification of Skin Cancer in Dermoscopy Images Using SAM-Based Deep Belief Networks
Syed Ziaur Rahman, Tejesh Reddy Singasani, K. S. Shaik
Healthcraft Frontiers (2023) Vol. 1, Iss. 1, pp. 15-32
Open Access | Times Cited: 2
CSR U-Net: A Novel Approach for Enhanced Skin Cancer Lesion Image Segmentation
V. Chakkarapani, S. Poornapushpakala
Lecture notes in networks and systems (2024), pp. 129-141
Closed Access
Multi- classification of skin lesions using a deep learning-based convolutional neural network
Khadija Shahzad, Muhammad Wasim, Ivan Miguel Pires, et al.
Procedia Computer Science (2024) Vol. 241, pp. 588-593
Open Access
LesionNet: an automated approach for skin lesion classification using SIFT features with customized convolutional neural network
Sarah A. Alzakari, Stephen Ojo, J. A. Wanliss, et al.
Frontiers in Medicine (2024) Vol. 11
Open Access
Addressing Challenges in Skin Cancer Diagnosis: A Convolutional Swin Transformer Approach
Sudha Paraddy, Virupakshappa Virupakshappa
Deleted Journal (2024)
Closed Access
Skin Cancer Image Classification Using Artificial Intelligence Strategies: A Systematic Review
Ricardo Vardasca, Joaquim Mendes, Carolina Magalhaes
Journal of Imaging (2024) Vol. 10, Iss. 11, pp. 265-265
Open Access
Analysis of Skin Lesions for Cancer Detection Using Convolutional Neural Networks
Katarzyna Korsak, Marcin Hernes, Ewa Walaszczyk, et al.
2022 12th International Conference on Advanced Computer Information Technologies (ACIT) (2023), pp. 574-578
Closed Access | Times Cited: 1
Skin Cancer Detection and Classification using Deep learning methods
Anchal Kumari, Punam Rattan
International Journal of Electrical and Electronics Research (2023) Vol. 11, Iss. 4, pp. 1072-1086
Open Access | Times Cited: 1
A Multitask Deep Learning Approach for Staples and Wound Segmentation in Abdominal Post-surgical Images
Gabriel Moyà-Alcover, Miquel Miró-Nicolau, Marc Munar, et al.
Lecture notes in computer science (2023), pp. 208-219
Closed Access
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