In image classification tasks, the evaluation of models’ robustness to increased dataset shifts with a probabilistic framework is very well studied. However, object detection (OD) tasks pose other challenges for uncertainty estimation and evaluation. For example, one needs to evaluate […]
When converting floating-point networks to low-precision equivalents for high-performance inference, the primary objective is to maximally compress the network whilst maintaining fidelity to the original, floating-point network. This is made particularly challenging when only a reduced or unlabelled dataset is […]
We present the challenges and lessons learned in implementing a custom intelligent vision system to detect types of grain and measure flow rate and morphology of grains going through a milling system.
The traditional approach for in-cabin-monitoring uses cameras that capture only visible or near-infrared (NIR) light and are designed to represent a scene as closely as possible to what a human expects to see at a constant frame rate. But visible […]
