Achieving robustness against adversarial attacks while maintaining high accuracy remains a
critical challenge in neural networks. Parameter quantization is one of the main approaches …

Many recent breakthroughs in machine learning have been enabled by the pre-trained
foundation models. By scaling up model parameters, training data, and computation …

This paper presents an in‐depth study and analysis of the assessment of English teaching
ability using the algorithm of fuzzy mean‐shift clustering. The paper proposes an automatic …

The application fields of traffic signs recognition are multiple, including autonomous
vehicles, self-driving cars, Advanced Driver Assistance Systems (ADAS), etc. The ultimate …

The amount of sensitive data stored on mobile devices has increased. Current mobile
device security schemas, such as pins, passwords, patterns, or even physiological …

Convolutional Neural Networks (CNN) are already being used to perform an increasing
number of object identification challenges. Most of the existing and new computer vision …

Road signs recognition plays an important role in improving traffic safety for both drivers and
pedestrians. To ensure this recognition, many approaches are proposed by researchers. To …

In our digital society, where the technology is changing at an accelerated rate, many of
human activities have become easier due to the exponential growth of many intelligent …

Road scene analysis is a wide domain of research that aims to ameliorate the environmental
perception in intelligent transportation systems, including autonomous vehicles and …

Abstract Vehicular Ad-hoc Network (VANET) is a new technology on which are based
Intelligent Transportation Systems (ITS). The goal of this technology is to improve the …