8 citations · 8 across the 1 of their papers we have counts for
7 papers
Utilising physics-guided deep learning to overcome data scarcity
Jinshuai Bai, Laith Alzubaidi, Qingxia Wang +3
Deep learning (DL) relies heavily on data, and the quality of data influences its performance significantly. However, obtaining high-quality, well-annotated datasets can be challen…
VGS-ATD: Robust Distributed Learning for Multi-Label Medical Image Classification Under Heterogeneous and Imbalanced Conditions
Zehui Zhao, Laith Alzubaidi, Haider A. Alwzwazy +2
In recent years, advanced deep learning architectures have shown strong performance in medical imaging tasks. However, the traditional centralized learning paradigm poses serious p…
A Review on Deep Learning Autoencoder in the Design of Next-Generation Communication Systems
Omar Alnaseri, Laith Alzubaidi, Yassine Himeur +3
Traditional mathematical models used in designing next-generation communication systems often fall short due to inherent simplifications, narrow scope, and computational limitation…
Transfer or Self-Supervised? Bridging the Performance Gap in Medical Imaging
Zehui Zhao, Laith Alzubaidi, Jinglan Zhang +3
Recently, transfer learning and self-supervised learning have gained significant attention within the medical field due to their ability to mitigate the challenges posed by limited…
Investigating Imperceptibility of Adversarial Attacks on Tabular Data: An Empirical Analysis
Zhipeng He, Chun Ouyang, Laith Alzubaidi +2
Adversarial attacks are a potential threat to machine learning models by causing incorrect predictions through imperceptible perturbations to the input data. While these attacks ha…
A Scalable and Generalized Deep Learning Framework for Anomaly Detection in Surveillance Videos
Sabah Abdulazeez Jebur, Khalid A. Hussein, Haider Kadhim Hoomod +3
Anomaly detection in videos is challenging due to the complexity, noise, and diverse nature of activities such as violence, shoplifting, and vandalism. While deep learning (DL) has…