Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

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:

Assessing the impact of data augmentation and a combination of CNNs on leukemia classification
Maíla L. Claro, Rodrigo Veras, André M. Santana, et al.
Information Sciences (2022) Vol. 609, pp. 1010-1029
Closed Access | Times Cited: 28

Showing 1-25 of 28 citing articles:

Lightweight EfficientNetB3 Model based on Depthwise Separable Convolutions for Enhancing Classification of Leukemia White Blood Cell Images
Amreen Batool, Yung-Cheol Byun
IEEE Access (2023) Vol. 11, pp. 37203-37215
Open Access | Times Cited: 48
Deep Learning for the Detection of Acute Lymphoblastic Leukemia Subtypes on Microscopic Images: A Systematic Literature Review
Tanzilal Mustaqim, Chastine Fatichah, Nanik Suciati
IEEE Access (2023) Vol. 11, pp. 16108-16127
Open Access | Times Cited: 27
Hematologic cancer diagnosis and classification using machine and deep learning: State-of-the-art techniques and emerging research directives
Hema J Patel, Himal Shah, Gayatri Patel, et al.
Artificial Intelligence in Medicine (2024) Vol. 152, pp. 102883-102883
Closed Access | Times Cited: 6
A supervised data augmentation strategy based on random combinations of key features
Yongchang Ding, Chang Liu, Haifeng Zhu, et al.
Information Sciences (2023) Vol. 632, pp. 678-697
Open Access | Times Cited: 15
Multiscale adaptive and attention-dilated convolutional neural network for efficient leukemia detection model with multiscale trans-res-Unet3+ -based segmentation network
K Gokulkannan, T A Mohanaprakash, J. DafniRose, et al.
Biomedical Signal Processing and Control (2024) Vol. 90, pp. 105847-105847
Closed Access | Times Cited: 5
Advancing Early Leukemia Diagnostics: A Comprehensive Study Incorporating Image Processing and Transfer Learning
Rezaul Haque, Abdullah Al Sakib, Md. Forhad Hossain, et al.
BioMedInformatics (2024) Vol. 4, Iss. 2, pp. 966-991
Open Access | Times Cited: 5
FocusAugMix: A Data Augmentation Method for Enhancing Acute Lymphoblastic Leukemia Classification
Tanzilal Mustaqim, Chastine Fatichah, Nanik Suciati, et al.
Intelligent Systems with Applications (2025), pp. 200512-200512
Open Access
H-Net: A dual-decoder enhanced FCNN for automated biomedical image diagnosis
Xiaogen Zhou, Xingqing Nie, Zhiqiang Li, et al.
Information Sciences (2022) Vol. 613, pp. 575-590
Closed Access | Times Cited: 18
Feature Fusion Based Ensemble of Deep Networks for Acute Leukemia Diagnosis Using Microscopic Smear Images
Md Hasib Al Muzdadid Haque Himel, Md. Al Mehedi Hasan, Taro Suzuki, et al.
IEEE Access (2024) Vol. 12, pp. 54758-54771
Open Access | Times Cited: 3
A hybrid detection model for acute lymphocytic leukemia using support vector machine and particle swarm optimization (SVM-PSO)
Lama K. Alsaykhan, Mashael Maashi
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 3
ODRNN: optimized deep recurrent neural networks for automatic detection of leukaemia
K. Dhana Shree, S. Logeswari
Signal Image and Video Processing (2024) Vol. 18, Iss. 5, pp. 4157-4173
Open Access | Times Cited: 2
A lightweight deep learning model for acute myeloid leukemia-related blast cell identification
Bing Leng, Hao Jiang, Bidou Wang, et al.
The Journal of Supercomputing (2024)
Closed Access | Times Cited: 2
Development of brain tumor radiogenomic classification using GAN-based augmentation of MRI slices in the newly released gazi brains dataset
M M Enes Yurtsever, Yılmaz Atay, Bilgehan Arslan, et al.
BMC Medical Informatics and Decision Making (2024) Vol. 24, Iss. 1
Open Access | Times Cited: 2
Efficient improvement of classification accuracy via selective test-time augmentation
Jongwook Son, Seokho Kang
Information Sciences (2023) Vol. 642, pp. 119148-119148
Closed Access | Times Cited: 5
Assessing the impact of Eight EfficientNetB (0- 7) Models for Leukemia Categorization
Kanwarpartap Singh Gill, Avinash Sharma, Vatsala Anand, et al.
(2023)
Closed Access | Times Cited: 4
γ-polyglutamic acid fermentation monitoring with ATR-FTIR spectroscopy based on a shallow convolutional neural network combined with data augmentation and attention module
Peng Shan, L. Liu, Guoxin Feng, et al.
Chemometrics and Intelligent Laboratory Systems (2023) Vol. 240, pp. 104899-104899
Closed Access | Times Cited: 4
ODRNN: Optimized Deep Recurrent Neural Networks for Automatic Detection of Leukaemia
K. Dhana Shree, S. Logeswari
Research Square (Research Square) (2024)
Open Access | Times Cited: 1
Leukemia Classification Using EfficientNetB5: A Deep Learning Approach
Aseel Alshoraihy, Anagheem Ibrahim, Housam Hasan Bou Issa
(2024), pp. 929-931
Closed Access | Times Cited: 1
Improving the generalizability of white blood cell classification with few-shot domain adaptation
Manon Chossegros, François Delhommeau, Daniel Stockholm, et al.
Journal of Pathology Informatics (2024) Vol. 15, pp. 100405-100405
Open Access | Times Cited: 1
A New Model for Blood Cancer Classification Based on Deep Learning Techniques
Hagar Ibrahim Mohamed, Fahad Kamal Elsheref, Shrouk Reda Kamal
International Journal of Advanced Computer Science and Applications (2023) Vol. 14, Iss. 6
Open Access | Times Cited: 3
Comparison of Different Methods for Building Ensembles of Convolutional Neural Networks
Loris Nanni, Andrea Loreggia, Sheryl Brahnam
Electronics (2023) Vol. 12, Iss. 21, pp. 4428-4428
Open Access | Times Cited: 2
Segmentation and classification of lymphoblastic leukaemia using quantum neural network
Javeria Amin, Muhammad Almas Anjum, Senka Krivić, et al.
Expert Systems (2022)
Closed Access | Times Cited: 4
RETRACTED: ODRNN: Optimized Deep Recurrent Neural Networks for Automatic Detection of Leukaemia
Anagha Shree, S. Logeswari, b
Egyptian Informatics Journal (2024) Vol. 26, pp. 100453-100453
Open Access
A Chronological Overview of Using Deep Learning for Leukemia Detection: A Scoping Review
Jorge Rubinos Rodriguez, Santiago Fernández, Nicholas Swartz, et al.
Cureus (2024)
Open Access
Vision Transformer Features-Based Leukemia Classification
Karima Ben-Suliman, Adam Krzyżak
Lecture notes in computer science (2024), pp. 111-120
Closed Access
Page 1 - Next Page

Scroll to top