Collision avoidance systems can play a vital role in reducing the number of accidents and
saving human lives. In this paper, we introduce and validate a novel method for vehicles …

In this research, we focus on developing an autonomous system for multiship collision
avoidance. The proposed approach combines global path planning based on deep …

Due to the sensor technology, video surveillance has become the main way for security
control in every big city in the world. Surveillance is usually used by governments for …

Deep learning has been rapidly growing in recent years obtaining excellent results for many
computer vision applications, such as image classification and object detection. One aspect …

Reinforcement learning can enable complex, adaptive behavior to be learned automatically
for autonomous robotic platforms. However, practical deployment of reinforcement learning …

Collision-free movement of an autonomous vehicle using reinforcement learning | Proceedings
of the 10th European conference on Artificial intelligence skip to main content ACM Digital …

This research addresses the challenging problem of visual collision detection in very
complex and dynamic real physical scenes, specifically, the vehicle driving scenarios. This …

Recently, deep neural networks trained with Imitation-Learning techniques have managed
to successfully control autonomous cars in a variety of urban and highway environments …

With a growing number of drones, the risk of collision with other air traffic or fixed obstacles
increases. New safety measures are required to keep the operation of Unmanned Aerial …

The use of intelligent systems to prevent accidents and safety enhancement in vehicles is
becoming a requirement. Besides, the development of autonomous cars is progressing …