Detecting and classifying vehicles as objects from images and videos is challenging in
appearance-based representation, yet plays a significant role in the substantial real-time …

The widespread use of mobile devices and sensors has motivated data-driven applications
that can leverage the power of big data to benefit many aspects of our daily life, such as …

Federated Learning (FL) is an emerging distributed learning paradigm under privacy
constraint. Data heterogeneity is one of the main challenges in FL, which results in slow …

Advances in information and signal processing technologies have a significant impact on
autonomous driving (AD), improving driving safety while minimizing the efforts of human …

Cloud computing has been a main-stream computing service for years. Recently, with the
rapid development in urbanization, massive video surveillance data are produced at an …

In recent decades, automatic vehicle classification plays a vital role in intelligent
transportation systems and visual traffic surveillance systems. Especially in countries that …

With the advance of AI, road object detection has been a prominent topic in computer vision,
mostly using perspective cameras. Fisheye lens provides omnidirectional wide coverage for …

Traffic surveillance cameras are the eyes of the Intelligent Transportation Systems (ITS).
However, they are currently isolated and can only extract information from each of their fixed …

Pruning methods have shown to be effective at reducing the size of deep neural networks
while kee** accuracy almost intact. Among the most effective methods are those that …

In recent years traffic surveillance systems have begun leveraging fisheye lenses to
minimize the requisite number of cameras for comprehensive coverage of streets and …