Training the ISP: How Differentiable Imaging Improves Automotive AI
As vehicle perception systems become more dependent on AI, the image pipeline can no longer be treated as a fixed step before the neural network begins.
In this interview, Arm Technical Director – Imaging Alexis Lluis Gomez, explains how differentiable ISPs allow image processing parameters to be optimised directly against perception performance. From reducing manual tuning and adapting to new sensors, to helping preserve model accuracy across changing camera platforms, he explores how task-specific imaging could reshape the route from raw sensor data to production-ready automotive AI.