We introduce the first very large vehicle activity dataset for event and frame-based cameras. This dataset is composed of both synthetic and real-world dataset with more than 50hours of automotive recordings acquired with a 346 x 260 pixels DVS event camera.
The central research focus of the NeuRonICS lab is to understand the principles of brain computation and to apply this understanding in electronic systems for building intelligent systems. Engineers have a lot to learn about computation from the brain, which has evolved over billions of years to solve difficult engineering problems. Efficient, parallel, low-power computation is a hallmark of the brain, and to be able to replicate this in electronic systems is one of the goals of the lab. Research interests of the lab span a broad range of subjects such as ASIC/FPGA VLSI design, analog IC design, brain-inspired algorithms, computational neuroscience, machine learning, and event-based sensors.