Perception Algorithms

Perception algorithms are methods used by machines to interpret sensory data, such as images, sounds, or sensor readings. They process this information to identify objects, understand environments, and make decisions. For example, in autonomous cars, perception algorithms help detect pedestrians, other vehicles, and road signs. They combine techniques like pattern recognition and machine learning to analyze complex data quickly and accurately. Essentially, these algorithms enable machines to "see," "hear," and understand their surroundings, allowing for safe and effective operation in dynamic environments.