Ai-based intrusion detection systems for in-vehicle networks: A survey

S Rajapaksha, H Kalutarage, MO Al-Kadri… - ACM Computing …, 2023 - dl.acm.org
The Controller Area Network (CAN) is the most widely used in-vehicle communication
protocol, which still lacks the implementation of suitable security mechanisms such as …

Breaking the data barrier: a review of deep learning techniques for democratizing AI with small datasets

IH Rather, S Kumar, AH Gandomi - Artificial Intelligence Review, 2024 - Springer
Justifiably, while big data is the primary interest of research and public discourse, it is
essential to acknowledge that small data remains prevalent. The same technological and …

Revealing the invisible with model and data shrinking for composite-database micro-expression recognition

Z Xia, W Peng, HQ Khor, X Feng… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Composite-database micro-expression recognition is attracting increasing attention as it is
more practical for real-world applications. Though the composite database provides more …

[HTML][HTML] Domain-and task-specific transfer learning for medical segmentation tasks

R Zoetmulder, E Gavves, M Caan… - Computer Methods and …, 2022 - Elsevier
Background and objectives: Transfer learning is a valuable approach to perform medical
image segmentation in settings with limited cases available for training convolutional neural …

Learning to hash: a comprehensive survey of deep learning-based hashing methods

A Singh, S Gupta - Knowledge and Information Systems, 2022 - Springer
Explosive growth of big data demands efficient and fast algorithms for nearest neighbor
search. Deep learning-based hashing methods have proved their efficacy to learn advanced …

A novel multi-branch channel expansion network for garbage image classification

C Shi, R Xia, L Wang - IEEE access, 2020 - ieeexplore.ieee.org
Due to the lack of data available for training, deep learning hardly performed well in the field
of garbage image classification. We choose the TrashNet data set which is widely used in …

Improving projected fuzzy K-means clustering via robust learning

X Zhao, F Nie, R Wang, X Li - Neurocomputing, 2022 - Elsevier
Fuzzy K-Means clustering has been an attractive research area for many multimedia tasks.
Due to the interference of the noise and outliers, the performance of fuzzy K-Means …

Parallel recurrent convolutional neural networks-based music genre classification method for mobile devices

R Yang, L Feng, H Wang, J Yao, S Luo - IEEE Access, 2020 - ieeexplore.ieee.org
With the rapid development of the mobile internet of things (IoTs) and mobile sensing
devices, a large amount of mobile computing-oriented applications have attracted attention …

State-of-the-art development of complex systems and their simulation methods

Y Tang, L Li, X Liu - Complex system modeling and simulation, 2021 - ieeexplore.ieee.org
The research on complex systems is different from that on general systems because the
former must consider self-organization, emergence, uncertainty, predetermination, and …

Unsupervised discriminative projection for feature selection

R Wang, J Bian, F Nie, X Li - IEEE Transactions on Knowledge …, 2020 - ieeexplore.ieee.org
Feature selection is one of the most important techniques to deal with the high-dimensional
data for a variety of machine learning and data mining tasks, such clustering, classification …