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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:

DermoDeep-A classification of melanoma-nevus skin lesions using multi-feature fusion of visual features and deep neural network
Qaisar Abbas, M. Emre Celebi
Multimedia Tools and Applications (2019) Vol. 78, Iss. 16, pp. 23559-23580
Closed Access | Times Cited: 72

Showing 1-25 of 72 citing articles:

Malignant Melanoma Classification Using Deep Learning: Datasets, Performance Measurements, Challenges and Opportunities
Ahmad Naeem, Muhammad Shoaib Farooq, Adel Khelifi, et al.
IEEE Access (2020) Vol. 8, pp. 110575-110597
Open Access | Times Cited: 145
Melanoma and Nevus Skin Lesion Classification Using Handcraft and Deep Learning Feature Fusion via Mutual Information Measures
Jose A. Almaraz-Damian, Volodymyr Ponomaryov, Sergiy Sadovnychiy, et al.
Entropy (2020) Vol. 22, Iss. 4, pp. 484-484
Open Access | Times Cited: 143
Dermatologist-Level Classification of Skin Cancer Using Cascaded Ensembling of Convolutional Neural Network and Handcrafted Features Based Deep Neural Network
Akhilesh Sharma, Shamik Tiwari, Gaurav Aggarwal, et al.
IEEE Access (2022) Vol. 10, pp. 17920-17932
Open Access | Times Cited: 97
Skin Cancer Disease Detection Using Transfer Learning Technique
Javed Rashid, Maryam Ishfaq, Ghulam Ali, et al.
Applied Sciences (2022) Vol. 12, Iss. 11, pp. 5714-5714
Open Access | Times Cited: 75
The Role of Machine Learning and Deep Learning Approaches for the Detection of Skin Cancer
Tehseen Mazhar, Inayatul Haq, Allah Ditta, et al.
Healthcare (2023) Vol. 11, Iss. 3, pp. 415-415
Open Access | Times Cited: 65
A improved pooling method for convolutional neural networks
Lei Zhao, Zhonglin Zhang
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 25
AI-Driven Enhancement of Skin Cancer Diagnosis: A Two-Stage Voting Ensemble Approach Using Dermoscopic Data
Tsu‐Man Chiu, Yunchang Li, I-Chun Chi, et al.
Cancers (2025) Vol. 17, Iss. 1, pp. 137-137
Open Access | Times Cited: 1
Developed Newton-Raphson based deep features selection framework for skin lesion recognition
Muhammad Attique Khan, Muhammad Sharif, Tallha Akram, et al.
Pattern Recognition Letters (2019) Vol. 129, pp. 293-303
Closed Access | Times Cited: 131
Multi-features extraction based on deep learning for skin lesion classification
Samia Benyahia, Boudjelal Meftah, Olivier Lézoray
Tissue and Cell (2021) Vol. 74, pp. 101701-101701
Open Access | Times Cited: 87
SSD-KD: A self-supervised diverse knowledge distillation method for lightweight skin lesion classification using dermoscopic images
Yongwei Wang, Yuheng Wang, Jiayue Cai, et al.
Medical Image Analysis (2022) Vol. 84, pp. 102693-102693
Open Access | Times Cited: 66
A Novel Hybrid Deep Learning Approach for Skin Lesion Segmentation and Classification
Puneet Thapar, Manik Rakhra, Gerardo Cazzato, et al.
Journal of Healthcare Engineering (2022) Vol. 2022, pp. 1-21
Open Access | Times Cited: 63
Automatic Classification of Melanoma Skin Cancer with Deep Convolutional Neural Networks
Khalil Aljohani, Turki Turki
AI (2022) Vol. 3, Iss. 2, pp. 512-525
Open Access | Times Cited: 47
Avg-topk: A new pooling method for convolutional neural networks
Cüneyt Özdemir
Expert Systems with Applications (2023) Vol. 223, pp. 119892-119892
Closed Access | Times Cited: 31
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: 7
Fruits yield estimation using Faster R-CNN with MIoU
Santi Kumari Behera, Amiya Kumar Rath, Prabira Kumar Sethy
Multimedia Tools and Applications (2021) Vol. 80, Iss. 12, pp. 19043-19056
Closed Access | Times Cited: 48
A Review on Automated Cancer Detection in Medical Images using Machine Learning and Deep Learning based Computational Techniques: Challenges and Opportunities
Jatinder Manhas, Rachit Kumar Gupta, Partha Pratim Roy
Archives of Computational Methods in Engineering (2021) Vol. 29, Iss. 5, pp. 2893-2933
Closed Access | Times Cited: 47
SkinNet-16: A deep learning approach to identify benign and malignant skin lesions
Pronab Ghosh, Sami Azam, Ryana Quadir, et al.
Frontiers in Oncology (2022) Vol. 12
Open Access | Times Cited: 35
Melanoma Detection Using XGB Classifier Combined with Feature Extraction and K-Means SMOTE Techniques
Chih-Chi Chang, Yu-Zhen Li, Hui-Ching Wu, et al.
Diagnostics (2022) Vol. 12, Iss. 7, pp. 1747-1747
Open Access | Times Cited: 28
Light-Dermo: A Lightweight Pretrained Convolution Neural Network for the Diagnosis of Multiclass Skin Lesions
Abdul Rauf Baig, Qaisar Abbas, Riyad Almakki, et al.
Diagnostics (2023) Vol. 13, Iss. 3, pp. 385-385
Open Access | Times Cited: 19
Enhancing Skin Cancer Detection and Classification in Dermoscopic Images through Concatenated MobileNetV2 and Xception Models
Roseline Oluwaseun Ogundokun, Aiman Li, Ronke Seyi Babatunde, et al.
Bioengineering (2023) Vol. 10, Iss. 8, pp. 979-979
Open Access | Times Cited: 19
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
Incorporating clinical knowledge with constrained classifier chain into a multimodal deep network for melanoma detection
Yuheng Wang, Jiayue Cai, Daniel C. Louie, et al.
Computers in Biology and Medicine (2021) Vol. 137, pp. 104812-104812
Closed Access | Times Cited: 37
BF2SkNet: best deep learning features fusion-assisted framework for multiclass skin lesion classification
Muhammad Ajmal, Muhammad Attique Khan, Tallha Akram, et al.
Neural Computing and Applications (2022) Vol. 35, Iss. 30, pp. 22115-22131
Closed Access | Times Cited: 26
Assist-Dermo: A Lightweight Separable Vision Transformer Model for Multiclass Skin Lesion Classification
Qaisar Abbas, Yassine Daadaa, Umer Rashid, et al.
Diagnostics (2023) Vol. 13, Iss. 15, pp. 2531-2531
Open Access | Times Cited: 14
Mobile-HR: An Ophthalmologic-Based Classification System for Diagnosis of Hypertensive Retinopathy Using Optimized MobileNet Architecture
Muhammad Zaheer Sajid, Imran Qureshi, Qaisar Abbas, et al.
Diagnostics (2023) Vol. 13, Iss. 8, pp. 1439-1439
Open Access | Times Cited: 13
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