Neuromorphic Sensor

Neuromorphic sensors, mimicking biological vision systems, offer asynchronous, event-driven data acquisition, enabling high temporal resolution and low power consumption compared to traditional cameras. Current research focuses on developing efficient algorithms and model architectures, such as convolutional neural networks (CNNs) and spiking neural networks (SNNs), for processing the unique data streams generated by these sensors, particularly for applications like object detection, face analysis, and gesture recognition. This technology's low power requirements and high temporal resolution are driving significant interest in applications ranging from autonomous vehicles and robotics to wearable health monitoring and space-based sensing.