Driving in adverse weather conditions is a key challenge for autonomous vehicles (AV).
Typical scene perception models perform poorly in rainy, foggy, snowy, and cloudy …

Drone detection is an important yet challenging task in the context of object detection. The
development of robust and reliable drone detection systems requires large amounts of …

In the era of data-driven technologies, the need for diverse and high-quality datasets for
training and testing machine learning models has become increasingly critical. In this article …

The accuracy of weather scene recognition is critical in a world where weather affects every
aspect of our everyday lives, particularly in areas like intelligent transportation networks …

Recent advancements in machine learning, particularly in deep learning and object
detection, have significantly improved performance in various tasks, including image …

This study implements ensemble deep learning models for weather image classification.
Firstly, this study check the performance of 9 pre-train models, namely Xception, ResNet152 …

This paper classifies the simulations of homogeneous synthetic images, heterogeneous
synthetic hazy images, and original hazy images taken from CCTV (Close Circuit Television) …

Agriculture is among the most vulnerable industries due to the unpredictable climate in
recent years, which has severely impacted regular human lives. Therefore, changes have …

This dissertation investigated the application of Machine Learning (ML) in multiple radar
missions. With the increasing computational power and data availability, machine learning is …

Autonomous vehicle technology (AVT) relies on achieving exceptional safety and reliability,
especially under challenging weather conditions such as extreme rain, fog, and clouds. In …