Recent advancements in artificial intelligence (AI) have greatly improved the object
detection capabilities of autonomous vehicles, especially using convolutional neural …

In autonomous driving, vehicles are recognized by computer vision and image processing to
reduce the risk of accidents. However, traditional vehicle detection algorithms often struggle …

The perception of the complex road environment is a critical factor in autonomous driving,
which has become the research focus in intelligent vehicles. In this paper, a real-time front …

In self-driving cars, object detection algorithms are becoming increasingly important, and the
accurate and fast recognition of objects is critical to realize autonomous driving. The existing …

In order to achieve rapid and accurate detection of vehicle objects in complex traffic
conditions, we propose a novel vehicle detection method. Firstly, more contextual and small …

Deep learning-based classification and detection algorithms have emerged as a powerful
tool for vehicle detection in intelligent transportation systems. The limitations of the number …

To solve real-life problems for different smart city applications, using deep Neural Network,
such as parking occupancy detection, requires fine-tuning of these networks. For large …

Autonomous vehicles have been considered as one of the most important trending topics in
the domain of intelligent transportation systems. It is expected that most of the leading …

Autonomous vehicle has come to reach on the road; however accurate road perception in
real-time is one of the crucial factors towards its success. The greatest challenge in this …

Efficient vehicle detection has played an important role in Intelligent Transportation Systems
(ITS) in smart cities. With the development of the Convolutional Neural Network (CNN) for …