This article studies the merits of applying log-gradient input images to convolutional neural
networks (CNNs) for tinyML computer vision (CV). We show that log gradients enable:(i) …

Current computer vision (CV) systems use an image signal processing (ISP) unit to convert
the high resolution raw images captured by image sensors to visually pleasing RGB images …

In the field of autonomous driving, cameras are crucial sensors for providing information
about a vehicle's environment. Image quality refers to a camera system's ability to capture …

Convolutional neural networks (CNNs) are now widely deployed in a variety of computer
vision (CV) systems. These systems typically include an image signal processor (ISP), even …

Whilst Deep Neural Networks have been develo** swiftly, most of the research has been
focused on RGB image. This type of image has been traditionally optimised for human …

This paper introduces an end-to-end object detection hardware accelerator that directly
processes RAW video signals to generate detection results, enabling a holistic approach to …

The rapid progress in intelligent vehicle technology has led to a significant reliance on
computer vision and deep neural networks (DNNs) to improve road safety and driving …