Alzubaidi, Laith

Review of deep learning: concepts, CNN architectures, challenges, applications, future directions

Alzubaidi, L., Zhang, J., Humaidi, A. J., Al-Dujaili, A., Duan, Y., Al-Shamma, O., Santamaría, J., Fadhel, M. A., Al-Amidie, M., & Farhan, L. (2021) · Journal of Big Data

Advanced Neural Network ApplicationsNeural Networks and Applications

Cited by 7,906

A systematic review of trustworthy and explainable artificial intelligence in healthcare: Assessment of quality, bias risk, and data fusion

Albahri, A. S., Duhaim, A. M., Fadhel, M. A., Alnoor, A., Baqer, N. S., Alzubaidi, L., Albahri, O. S., Alamoodi, A. H., Bai, J., Salhi, A., et al. (2023) · Information Fusion

Explainable Artificial Intelligence (XAI)Artificial Intelligence in Healthcare and Education

Cited by 716

Towards a Better Understanding of Transfer Learning for Medical Imaging: A Case Study

Alzubaidi, L., Fadhel, M. A., Al-Shamma, O., Zhang, J., Santamaría, J., Duan, Y., & R. Oleiwi, S. (2020) · Applied Sciences

Domain Adaptation and Few-Shot LearningAdvanced Neural Network Applications

Cited by 258

Review of the State of the Art of Deep Learning for Plant Diseases: A Broad Analysis and Discussion

Hasan, R. I., Yusuf, S. M., & Alzubaidi, L. (2020) · Plants

Smart Agriculture and AIAdvanced Neural Network Applications

Cited by 213

Deep Learning Models for Classification of Red Blood Cells in Microscopy Images to Aid in Sickle Cell Anemia Diagnosis

Alzubaidi, L., Fadhel, M. A., Al-Shamma, O., Zhang, J., & Duan, Y. (2020) · Electronics

Digital Imaging for Blood DiseasesCell Image Analysis Techniques

Cited by 197

Optimizing the Performance of Breast Cancer Classification by Employing the Same Domain Transfer Learning from Hybrid Deep Convolutional Neural Network Model

Alzubaidi, L., Al-Shamma, O., Fadhel, M. A., Farhan, L., Zhang, J., & Duan, Y. (2020) · Electronics

AI in cancer detectionDigital Imaging for Blood Diseases

Cited by 143

Review on Deep Learning Approaches for Anomaly Event Detection in Video Surveillance

Jebur, S. A., Hussein, K. A., Hoomod, H. K., Alzubaidi, L., & Santamaría, J. (2022) · Electronics

Anomaly Detection Techniques and ApplicationsVideo Surveillance and Tracking Methods

Cited by 69

Robust application of new deep learning tools: an experimental study in medical imaging

Alzubaidi, L., Fadhel, M. A., Al-Shamma, O., Zhang, J., Santamaría, J., & Duan, Y. (2022) · Multimedia Tools and Applications

AI in cancer detectionAdvanced Neural Network Applications

Cited by 68

Fuzzy decision-making framework for explainable golden multi-machine learning models for real-time adversarial attack detection in Vehicular Ad-hoc Networks

Albahri, A. S., Hamid, R. A., Abdulnabi, A. R., Albahri, O. S., Alamoodi, A. H., Deveci, M., Pedrycz, W., Alzubaidi, L., Santamaría, J., & Gu, Y. (2024) · Information Fusion

Vehicular Ad Hoc Networks (VANETs)Adversarial Robustness in Machine Learning

Cited by 55

Face Recognition Based on Deep Learning and FPGA for Ethnicity Identification

AlBdairi, A. J. A., Xiao, Z., Alkhayyat, A., Humaidi, A. J., Fadhel, M. A., Taher, B. H., Alzubaidi, L., Santamaría, J., & Al-Shamma, O. (2022) · Applied Sciences

Face recognition and analysisAdvanced Neural Network Applications

Cited by 54

Boosting Convolutional Neural Networks Performance Based on FPGA Accelerator

Al-Shamma, O., Fadhel, M. A., Hameed, R. A., Alzubaidi, L., & Zhang, J. (2020) · Advances in Intelligent Systems and Computing

Advanced Neural Network ApplicationsEmbedded Systems Design Techniques

Cited by 27

Real-Time Sickle Cell Anemia Diagnosis Based Hardware Accelerator

Fadhel, M. A., Al-Shamma, O., Alzubaidi, L., & Oleiwi, S. R. (2020) · Communications in Computer and Information Science

Digital Imaging for Blood DiseasesEmbedded Systems and FPGA Applications

Cited by 5