How are neural networks applied in autonomous vehicles?

How are neural networks applied in autonomous vehicles?

Step 1: Understand that neural networks are a type of computer program that can learn from data.
Step 2: Recognize that autonomous vehicles need to understand their surroundings to drive safely.
Step 3: Learn that neural networks help these vehicles by analyzing images from cameras.
Step 4: Know that the neural networks identify important objects like pedestrians, other cars, and obstacles.
Step 5: Realize that this identification helps the vehicle make decisions, like when to stop or turn.

Object Detection – Neural networks are employed to recognize and classify objects in the vehicle's environment, such as pedestrians, vehicles, and obstacles.
Sensor Fusion – Neural networks can integrate data from various sensors (like cameras, LIDAR, and radar) to improve the accuracy of object detection.
Decision Making – Neural networks assist in making real-time decisions based on the detected objects and their movements.