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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:

Brain tumor segmentation and classification using hybrid deep CNN with LuNetClassifier
T. Balamurugan, E. Gnanamanoharan
Neural Computing and Applications (2022) Vol. 35, Iss. 6, pp. 4739-4753
Closed Access | Times Cited: 49

Showing 26-50 of 49 citing articles:

Revolutionizing Brain Tumor Diagnosis with Enhanced Deep Learning and Transfer Learning Algorithms
S.K. Kanagapriya, V.Vijeya Kaveri, S. Saraswathi, et al.
(2024), pp. 1-10
Closed Access
Brain tumour detection via EfficientDet and classification with DynaQ-GNN-LSTM
Ayesha Agrawal, Vinod Maan
Salud Ciencia y Tecnología (2024) Vol. 4, pp. 1079-1079
Closed Access
Advancing Precision Medicine: An Exploration of Hybrid Deep Learning Approaches for Automated Human Brain Tissue Segmentation and Tumour Localization in MRI Imaging
Mohammed Razia Alangir Banu, A. S. Gousia Banu
Advanced technologies and societal change (2024), pp. 137-148
Closed Access
Edge‐Preserved Tversky Indexive Hellinger with Deep Perceptive Czekanowski‐Based Image Classification
K. Ramalakshmi, Venkatesh Raghavan, Jayakumar Kaliappan, et al.
Journal of Sensors (2024) Vol. 2024, Iss. 1
Open Access
Brain Tumor Automated Detection System Based on Hybrid Deep Learning Networks Using MRI Images
Gerges M. Salama, Shady Ashraf, Esraa Salah Bayoumi, et al.
2022 International Telecommunications Conference (ITC-Egypt) (2024), pp. 72-77
Closed Access
Brain tumor recognition and classification techniques
Roaa Soloh, Ali Rammal, Mohamad El-Abed
Elsevier eBooks (2024), pp. 43-56
Closed Access
A systematic review of trending technologies in non-invasive automatic brain tumor detection
Jyoti Jyoti -, Anuj Kumar
Multimedia Tools and Applications (2024)
Closed Access
Segmentation and classification of brain tumor using Taylor fire hawk optimization enabled deep learning approach
Ajit Kumar Rout, D. Sumathi, S. Nandakumar, et al.
Electromagnetic Biology and Medicine (2024), pp. 1-22
Closed Access
FL-SiCNN: An improved brain tumor diagnosis using siamese convolutional neural network in a peer-to-peer federated learning approach
Ameer N. Onaizah, Yuanqing Xia, Khurram Hussain
Alexandria Engineering Journal (2024) Vol. 114, pp. 1-11
Open Access
DTAUE: A multi-input multi-branch decoupled semi-supervised 3D network based on threshold adaptive uncertainty estimation for echocardiography segmentation
Chendong Qin, Yongxiong Wang, Jiapeng Zhang
Biomedical Signal Processing and Control (2024) Vol. 101, pp. 107212-107212
Closed Access
Advancing multi-categorization and segmentation in brain tumors using novel efficient deep learning approaches
Nadenlla RajamohanReddy, G. Muneeswari
PeerJ Computer Science (2024) Vol. 10, pp. e2496-e2496
Open Access
A Hybrid Machine Learning and Deep Learning Approach for Brain Tumor Segmentation and Disease Type Prediction
Nada Abdul Kareem
Journal Européen des Systèmes Automatisés (2024) Vol. 57, Iss. 6, pp. 1573-1582
Closed Access
Performance of Convolutional Neural Network Models in Meningioma Segmentation in Magnetic Resonance Imaging: A Systematic Review and Meta-Analysis
Tingwei Wang, Jia‐Sheng Hong, Wei‐Kai Lee, et al.
Neuroinformatics (2024) Vol. 23, Iss. 1, pp. 1-12
Open Access
Design of an Iterative Cluster-Based Model for Detection of Brain Tumors Using Deep Transfer Learning Models
Yenumala Sankararao, Syed Khasim
Traitement du signal (2024) Vol. 41, Iss. 06, pp. 2909-2922
Closed Access
Adversarial Attack Detection with Convolutional Neural Networks on Images for Selection of the Most Suitable Model in Object Detection
Murat Taşyürek, Ertuğrul Gül
Iğdır Üniversitesi Fen Bilimleri Enstitüsü Dergisi (2023) Vol. 13, Iss. 4, pp. 2353-2363
Open Access | Times Cited: 1
Bayesian optimization-based CNN framework for automated detection of brain tumors
Mahır Kaya
Balkan Journal of Electrical and Computer Engineering (2023)
Open Access | Times Cited: 1
Segmentation and Detection of Brain Tumors using EfficientNetB3 Model
Menka Vishwakarma, Pradeep Tripathi, Bhanu Pratap Singh, et al.
(2023) Vol. 18, pp. 1463-1470
Closed Access | Times Cited: 1
Apply Agglomerative Algorithm and Vgg16 on Brain Tumor Segmentation (Dataset to be Used Brats)
Lakshmi Namratha Vempaty, Manjusha Tatiya, Anurag Shrivastava, et al.
(2023) Vol. 16, pp. 1602-1607
Closed Access | Times Cited: 1
Brain tumor magnetic resonance images enhanced by hybrid method based on deep learning paradigm
Mehmet Gül, Yılmaz Kaya
Research Square (Research Square) (2023)
Open Access
A Short Literature Review of Brain Tumour Segmentation and Classification Framework: Challenges Issues and Future Scope
K S Adarsh, R. Gowri Manohari, Jayesh George M
2022 6th International Conference on Trends in Electronics and Informatics (ICOEI) (2023)
Closed Access
Advancements and emerging trends in brain tumor classification using MRI: a systematic review
Asmita Dixit, Manish Thakur
Network Modeling Analysis in Health Informatics and Bioinformatics (2023) Vol. 12, Iss. 1
Closed Access
Review of deep learning-driven MRI brain tumor detection and segmentation methods
Rong Zhang, Hongliang Luo, Weijie Chen, et al.
Advances in Computer Signals and Systems (2023) Vol. 7, Iss. 8, pp. 17-28
Open Access
Brain tumor Segmentation and Classification using SMA based Modified HBTNet Model from MRI images
Garvit Vyas, Jagadevi N. Kalshetty, Piyush Kumar Pareek
(2023), pp. 1-9
Closed Access
Brain Tumour Segmentation and Classification Using the Convolutional Neural Network (U- Net Model)
Yogesh Kumar B, Veena S Badiger, Sheetal Sheetal, et al.
(2023), pp. 258-265
Closed Access
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