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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:

Detection and classification of normal and abnormal patterns in mammograms using deep neural network
R. M. Suresh, A. Nagaraja Rao, B. Eswara Reddy
Concurrency and Computation Practice and Experience (2019) Vol. 31, Iss. 14
Closed Access | Times Cited: 22

Showing 22 citing articles:

A novel hybrid deep learning method for early detection of lung cancer using neural networks
Shalini Wankhade, S. Vigneshwari
Healthcare Analytics (2023) Vol. 3, pp. 100195-100195
Open Access | Times Cited: 51
Lung Infection Segmentation for COVID-19 Pneumonia Based on a Cascade Convolutional Network from CT Images
Ramin Ranjbarzadeh, Saeid Jafarzadeh Ghoushchi, Malika Bendechache, et al.
BioMed Research International (2021) Vol. 2021, pp. 1-16
Open Access | Times Cited: 84
Computer Vision-Based Microcalcification Detection in Digital Mammograms Using Fully Connected Depthwise Separable Convolutional Neural Network
Khalil ur Rehman, Jianqiang Li, Yan Pei, et al.
Sensors (2021) Vol. 21, Iss. 14, pp. 4854-4854
Open Access | Times Cited: 49
Diagnostic Strategies for Breast Cancer Detection: From Image Generation to Classification Strategies Using Artificial Intelligence Algorithms
Jesus A. Basurto-Hurtado, Irving A. Cruz‐Albarran, Manuel Toledano‐Ayala, et al.
Cancers (2022) Vol. 14, Iss. 14, pp. 3442-3442
Open Access | Times Cited: 23
Breast Cancer Mass Detection in Mammograms Using Gray Difference Weight and MSER Detector
B. V. Divyashree, G. Hemantha Kumar
SN Computer Science (2021) Vol. 2, Iss. 2
Closed Access | Times Cited: 16
Segmentation of malignant tumours in mammogram images: A hybrid approach using convolutional neural networks and connected component analysis
Abhijit Roy, Bikesh Kumar Singh, Sumit K. Banchhor, et al.
Expert Systems (2021) Vol. 39, Iss. 1
Closed Access | Times Cited: 10
Intelligent Deep Data Analytics Based Remote Sensing Scene Classification Model
Ahmed Althobaiti, Abdullah Alhumaidi Alotaibi, S. Abdel‐Khalek, et al.
Computers, materials & continua/Computers, materials & continua (Print) (2022) Vol. 72, Iss. 1, pp. 1921-1938
Open Access | Times Cited: 6
Novel technique for caries detection using curvilinear semantic deep convolutional neural network
M. V. Rajee, C. Mythili
Multimedia Tools and Applications (2022) Vol. 82, Iss. 7, pp. 10745-10762
Closed Access | Times Cited: 5
Lightweight efficient network for defect classification of polarizers
Ruizhen Liu, Zhiyi Sun, Anhong Wang, et al.
Concurrency and Computation Practice and Experience (2020) Vol. 32, Iss. 11
Closed Access | Times Cited: 6
Internet of Things and Cloud Enabled Hybrid Feature Extraction with Adaptive Neuro Fuzzy Inference System for Diabetic Retinopathy Diagnosis
K. Parthiban, K. Venkatachalapathy
Journal of Computational and Theoretical Nanoscience (2020) Vol. 17, Iss. 12, pp. 5261-5269
Closed Access | Times Cited: 6
A review on machine learning techniques for the assessment of image grading in breast mammogram
Khalil ur Rehman, Jianqiang Li, Yan Pei, et al.
International Journal of Machine Learning and Cybernetics (2022) Vol. 13, Iss. 9, pp. 2609-2635
Closed Access | Times Cited: 4
Breast Cancer Detection Using Deep Belief Network by Applying Feature Extraction on Various Classifiers
Et. al. Prasath Alias Surendhar S
Türk bilgisayar ve matematik eğitimi dergisi (2021) Vol. 12, Iss. 1S, pp. 471-487
Open Access | Times Cited: 5
Comparison of the histogram of oriented gradient, GLCM, and shape feature extraction methods for breast cancer classification using SVM
Hanimatim Mu'jizah, Dian Candra Rini Novitasari
Jurnal Teknologi dan Sistem Komputer (2021) Vol. 9, Iss. 3, pp. 150-156
Open Access | Times Cited: 5
Breast Cancer Detection: Challenges and Future Research Developments
Amarjeet Poonia, Virendra Kumar Sharma, Hari Singh, et al.
(2024), pp. 1-6
Closed Access
Performance Analysis of Breast Cancer Detection Method Using ANFIS Classification Approach
K. Nagalakshmi, S. Dr. Suriya
Computer Systems Science and Engineering (2022) Vol. 44, Iss. 1, pp. 501-517
Open Access | Times Cited: 3
Optimized textural features for mass classification in digital mammography using a weighted average gravitational search algorithm
Oludare Y. Ogundepo, Isaac O. A. Omeiza, Jonathan Ponmile Oguntoye
International Journal of Power Electronics and Drive Systems/International Journal of Electrical and Computer Engineering (2022) Vol. 12, Iss. 5, pp. 5001-5001
Open Access | Times Cited: 3
Mammographic Image Classification Using Deep Neural Network for Computer-Aided Diagnosis
Charles Arputham, Krishnaraj Nagappan, Lenin Babu Russeliah, et al.
Intelligent Automation & Soft Computing (2021) Vol. 27, Iss. 3, pp. 747-759
Open Access | Times Cited: 4
Preparation of Patient Mammogram Images for Segmentation
Esther Chiadikaobi Ugwueke, Dimitrios Palogiannidis
(2023), pp. 305-307
Closed Access | Times Cited: 1
Breast Lesion Classification using Radiomics-derived Regions of Interest on Mammograms
Shubham Gujar, Xiaomeng Lei, Steven Cen, et al.
(2023), pp. 1-5
Closed Access | Times Cited: 1
Segmentation-Based Fractal Texture Analysis (SFTA) to Detect Mass in Mammogram Images
Irma Amelia Dewi, Nur Fitrianti Fahrudin, J.P. Raina
ELKOMIKA Jurnal Teknik Energi Elektrik Teknik Telekomunikasi & Teknik Elektronika (2021) Vol. 9, Iss. 1, pp. 203-203
Open Access | Times Cited: 3
Multi-Type Classification Comparison of Mammogram Abnormalities
S. Sowmyayani, V. Murugan
International Journal of Image and Graphics (2020) Vol. 21, Iss. 03, pp. 2150027-2150027
Closed Access | Times Cited: 1
Optimized Deep Learning-Based Fully Resolution Convolution Neural Network for Breast Tumour Segmentation on Field Programmable Gate Array
Sharada Guptha M N, M. N. Eshwarappa
Computer Methods in Biomechanics and Biomedical Engineering Imaging & Visualization (2023) Vol. 11, Iss. 5, pp. 2050-2069
Closed Access
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