A comprehensive review on artificial intelligence/machine learning algorithms for empowering the future IoT toward 6G era

MR Mahmood, MA Matin, P Sarigiannidis… - IEEE …, 2022 - ieeexplore.ieee.org
The evolution of the wireless network systems over decades has been providing new
services to the users with the help of innovative network and device technologies. In recent …

Vision transformer architecture and applications in digital health: a tutorial and survey

K Al-Hammuri, F Gebali, A Kanan… - Visual computing for …, 2023 - Springer
The vision transformer (ViT) is a state-of-the-art architecture for image recognition tasks that
plays an important role in digital health applications. Medical images account for 90% of the …

Transformers and large language models for efficient intrusion detection systems: A comprehensive survey

H Kheddar - arxiv preprint arxiv:2408.07583, 2024 - arxiv.org
With significant advancements in Transformers LLMs, NLP has extended its reach into many
research fields due to its enhanced capabilities in text generation and user interaction. One …

A hybrid parallel deep learning model for efficient intrusion detection based on metric learning

S Cai, D Han, X Yin, D Li, CC Chang - Connection Science, 2022 - Taylor & Francis
With the rapid development of network technology, a variety of new malicious attacks appear
while attack methods are constantly updated. As the attackers exploit the vulnerabilities of …

A blockchain-based secure storage scheme for medical information

Z Sun, D Han, D Li, X Wang, CC Chang… - EURASIP Journal on …, 2022 - Springer
Medical data involves a large amount of personal information and is highly privacy sensitive.
In the age of big data, the increasing informatization of healthcare makes it vital that medical …

Few-Shot network intrusion detection based on prototypical capsule network with attention mechanism

H Sun, L Wan, M Liu, B Wang - Plos one, 2023 - journals.plos.org
Network intrusion detection plays a crucial role in ensuring network security by
distinguishing malicious attacks from normal network traffic. However, imbalanced data …

Object detection using convolutional neural networks and transformer-based models: a review

S Shah, J Tembhurne - Journal of Electrical Systems and Information …, 2023 - Springer
Transformer models are evolving rapidly in standard natural language processing tasks;
however, their application is drastically proliferating in computer vision (CV) as well …

An reinforcement learning-based speech censorship chatbot system

S Cai, D Han, D Li, Z Zheng, N Crespi - The Journal of Supercomputing, 2022 - Springer
The rapid development of artificial intelligence (AI) technology has enabled large-scale AI
applications to land in the market and practice. However, plenty of security issues have been …

[PDF][PDF] Synergy of Graph-Based Sentence Selection and Transformer Fusion Techniques For Enhanced Text Summarization Performance

YR Gogireddy, AN Bandaru… - Journal of Computer …, 2024 - researchgate.net
This paper presents a new method to improve text summarization by combining the
strengths of Graph Neural Networks with Transformer-based models. Text summarization is …

Integration of Mixture of Experts and Multimodal Generative AI in Internet of Vehicles: A Survey

M Xu, D Niyato, J Kang, Z **ong, A Jamalipour… - arxiv preprint arxiv …, 2024 - arxiv.org
Generative AI (GAI) can enhance the cognitive, reasoning, and planning capabilities of
intelligent modules in the Internet of Vehicles (IoV) by synthesizing augmented datasets …