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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:

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

Showing 1-25 of 131 citing articles:

Multimodal Brain Tumor Classification Using Deep Learning and Robust Feature Selection: A Machine Learning Application for Radiologists
Muhammad Attique Khan, Imran Ashraf, Majed Alhaisoni, et al.
Diagnostics (2020) Vol. 10, Iss. 8, pp. 565-565
Open Access | Times Cited: 338
Attributes based skin lesion detection and recognition: A mask RCNN and transfer learning-based deep learning framework
Muhammad Attique Khan, Tallha Akram, Yudong Zhang, et al.
Pattern Recognition Letters (2021) Vol. 143, pp. 58-66
Closed Access | Times Cited: 205
A decision support system for multimodal brain tumor classification using deep learning
Muhammad Imran Sharif, Muhammad Attique Khan, Musaed Alhussein, et al.
Complex & Intelligent Systems (2021) Vol. 8, Iss. 4, pp. 3007-3020
Open Access | Times Cited: 187
Fusion of U-Net and CNN model for segmentation and classification of skin lesion from dermoscopy images
Vatsala Anand, Sheifali Gupta, Deepika Koundal, et al.
Expert Systems with Applications (2022) Vol. 213, pp. 119230-119230
Closed Access | Times Cited: 168
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
Pixels to Classes: Intelligent Learning Framework for Multiclass Skin Lesion Localization and Classification
Muhammad Attique Khan, Yudong Zhang, Muhammad Sharif, et al.
Computers & Electrical Engineering (2021) Vol. 90, pp. 106956-106956
Closed Access | Times Cited: 133
Improving Effectiveness of Different Deep Transfer Learning-Based Models for Detecting Brain Tumors From MR Images
Sohaib Asif, Wenhui Yi, Qurrat Ul Ain, et al.
IEEE Access (2022) Vol. 10, pp. 34716-34730
Open Access | Times Cited: 124
A review of deep learning-based multiple-lesion recognition from medical images: classification, detection and segmentation
Huiyan Jiang, Zhaoshuo Diao, Tianyu Shi, et al.
Computers in Biology and Medicine (2023) Vol. 157, pp. 106726-106726
Closed Access | Times Cited: 113
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: 99
DermoExpert: Skin lesion classification using a hybrid convolutional neural network through segmentation, transfer learning, and augmentation
Md. Kamrul Hasan, Md. Toufick E Elahi, Md. Ashraful Alam, et al.
Informatics in Medicine Unlocked (2022) Vol. 28, pp. 100819-100819
Open Access | Times Cited: 98
Multimodal brain tumor detection and classification using deep saliency map and improved dragonfly optimization algorithm
Muhammad Attique Khan, Awais Khan, Majed Alhaisoni, et al.
International Journal of Imaging Systems and Technology (2022) Vol. 33, Iss. 2, pp. 572-587
Closed Access | Times Cited: 83
Classification of skin cancer from dermoscopic images using deep neural network architectures
S. M. Jaisakthi, P Mirunalini, Chandrabose Aravindan, et al.
Multimedia Tools and Applications (2022) Vol. 82, Iss. 10, pp. 15763-15778
Open Access | Times Cited: 82
Multiclass skin lesion localization and classification using deep learning based features fusion and selection framework for smart healthcare
Sarmad Maqsood, Robertas Damaševičius
Neural Networks (2023) Vol. 160, pp. 238-258
Closed Access | Times Cited: 78
Skin-Net: a novel deep residual network for skin lesions classification using multilevel feature extraction and cross-channel correlation with detection of outlier
Yousef S. Alsahafi, Mohamed A. Kassem, Khalid M. Hosny
Journal Of Big Data (2023) Vol. 10, Iss. 1
Open Access | Times Cited: 69
An enhanced deep learning method for multi-class brain tumor classification using deep transfer learning
Sohaib Asif, Ming Zhao, Fengxiao Tang, et al.
Multimedia Tools and Applications (2023) Vol. 82, Iss. 20, pp. 31709-31736
Closed Access | Times Cited: 63
Skin Lesion Analysis and Cancer Detection Based on Machine/Deep Learning Techniques: A Comprehensive Survey
Mehwish Zafar, Muhammad Imran Sharif, Muhammad Irfan Sharif, et al.
Life (2023) Vol. 13, Iss. 1, pp. 146-146
Open Access | Times Cited: 47
LBO-MPAM: Ladybug Beetle Optimization-based multilayer perceptron attention module for segmenting the skin lesion and automatic localization
V. Sellam, Kannan Natrajan, Senthil Pandi S, et al.
Journal of Experimental & Theoretical Artificial Intelligence (2024), pp. 1-26
Closed Access | Times Cited: 25
Gastrointestinal diseases segmentation and classification based on duo-deep architectures
Mehshan Ahmed Khan, Muhammad Attique Khan, Fawad Ahmed, et al.
Pattern Recognition Letters (2019) Vol. 131, pp. 193-204
Closed Access | Times Cited: 139
Classification of stomach infections: A paradigm of convolutional neural network along with classical features fusion and selection
Abdul Majid, Muhammad Attique Khan, Mussarat Yasmin, et al.
Microscopy Research and Technique (2020) Vol. 83, Iss. 5, pp. 562-576
Closed Access | Times Cited: 133
Computer-Aided Gastrointestinal Diseases Analysis From Wireless Capsule Endoscopy: A Framework of Best Features Selection
Muhammad Attique Khan, Seifedine Kadry, Majed Alhaisoni, et al.
IEEE Access (2020) Vol. 8, pp. 132850-132859
Open Access | Times Cited: 131
Detection of Skin Diseases from Dermoscopy Image Using the combination of Convolutional Neural Network and One-versus-All
Kemal Polat, Kaan Onur Koç
Journal of Artificial Intelligence and Systems (2020) Vol. 2, Iss. 1, pp. 80-97
Open Access | Times Cited: 94
A two‐stream deep neural network‐based intelligent system for complex skin cancer types classification
Muhammad Attique Khan, Muhammad Sharif, Tallha Akram, et al.
International Journal of Intelligent Systems (2021) Vol. 37, Iss. 12, pp. 10621-10649
Open Access | Times Cited: 93
A multilevel features selection framework for skin lesion classification
Tallha Akram, Hafiz Muhammad Junaid Lodhi, Syed Rameez Naqvi, et al.
Human-centric Computing and Information Sciences (2020) Vol. 10, Iss. 1
Open Access | Times Cited: 87
Intelligent fusion-assisted skin lesion localization and classification for smart healthcare
Muhammad Attique Khan, Khan Muhammad, Muhammad Sharif, et al.
Neural Computing and Applications (2021) Vol. 36, Iss. 1, pp. 37-52
Closed Access | Times Cited: 87
Deep learning based classification of facial dermatological disorders
Evgin Göçeri
Computers in Biology and Medicine (2020) Vol. 128, pp. 104118-104118
Closed Access | Times Cited: 81
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