|
|
|
|
|
Ioana Branescu, Octavian Grigorescu and Mihai Dascalu
Effectively understanding and categorizing vulnerabilities is vital in the ever-evolving cybersecurity landscape, since only one exposure can have a devastating effect on the entire system. Given the increasingly massive number of threats and the size of...
ver más
|
|
|
|
|
|
|
|
|
|
|
Andrei Paraschiv, Teodora Andreea Ion and Mihai Dascalu
The advent of online platforms and services has revolutionized communication, enabling users to share opinions and ideas seamlessly. However, this convenience has also brought about a surge in offensive and harmful language across various communication m...
ver más
|
|
|
|
|
|
|
|
|
|
|
Carlo Galli, Nikolaos Donos and Elena Calciolari
Systematic reviews are cumbersome yet essential to the epistemic process of medical science. Finding significant reports, however, is a daunting task because the sheer volume of published literature makes the manual screening of databases time-consuming....
ver más
|
|
|
|
|
|
|
|
|
|
|
Jiaming Li, Ning Xie and Tingting Zhao
In recent years, with the rapid advancements in Natural Language Processing (NLP) technologies, large models have become widespread. Traditional reinforcement learning algorithms have also started experimenting with language models to optimize training. ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Utpal Barman, Parismita Sarma, Mirzanur Rahman, Vaskar Deka, Swati Lahkar, Vaishali Sharma and Manob Jyoti Saikia
Invading pests and diseases always degrade the quality and quantity of plants. Early and accurate identification of plant diseases is critical for plant health and growth. This work proposes a smartphone-based solution using a Vision Transformer (ViT) mo...
ver más
|
|
|
|
|
|
|
|
|
|
|
Chenglin Yang, Dongliang Xu and Xiao Ma
Due to the increasing severity of network security issues, training corresponding detection models requires large datasets. In this work, we propose a novel method based on generative adversarial networks to synthesize network data traffic. We introduced...
ver más
|
|
|
|
|
|
|
|
|
|
|
Weiying Wang and Toshihiro Osaragi
The generation and prediction of daily human mobility patterns have raised significant interest in many scientific disciplines. Using various data sources, previous studies have examined several deep learning frameworks, such as the RNN and GAN, to synth...
ver más
|
|
|
|
|
|
|
|
|
|
|
Mihael Gudlin, Miro Hegedic, Matija Golec and Davor Kolar
In the quest for industrial efficiency, human performance within manufacturing systems remains pivotal. Traditional time study methods, reliant on direct observation and manual video analysis, are increasingly inadequate, given technological advancements...
ver más
|
|
|
|
|
|
|
|
|
|
|
Hamed Alshammari, Ahmed El-Sayed and Khaled Elleithy
The effectiveness of existing AI detectors is notably hampered when processing Arabic texts. This study introduces a novel AI text classifier designed specifically for Arabic, tackling the distinct challenges inherent in processing this language. A parti...
ver más
|
|
|
|
|
|
|
|
|
|
|
Nils Hütten, Miguel Alves Gomes, Florian Hölken, Karlo Andricevic, Richard Meyes and Tobias Meisen
Quality assessment in industrial applications is often carried out through visual inspection, usually performed or supported by human domain experts. However, the manual visual inspection of processes and products is error-prone and expensive. It is ther...
ver más
|
|
|
|
|
|