Survey of Autonomous Vehicles' Collision Avoidance Algorithms.

Since the field of autonomous vehicles is developing quickly, it is becoming increasingly crucial for them to safely and effectively navigate their surroundings to avoid collisions. The primary collision avoidance algorithms currently employed by self-driving cars are examined in this thorough survey. It looks into several methods, such as sensor-based methods for precise obstacle identification, sophisticated path-planning algorithms that guarantee cars follow dependable and safe paths, and decision-making systems that allow for adaptable reactions to a range of driving situations.

An Efficient Attentional Image Dehazing Deep Network Using Two Color Space (ADMC-net).

Image dehazing has become a crucial prerequisite for most outdoor computer applications. The majority of existing dehazing models can achieve the haze removal problem. However, they fail to preserve colors and fine details.