Robust localisation and identification of vertebrae is essential for automated spine analysis.
The contribution of this work to the task is two-fold:(1) Inspired by the human expert, we …

Rationale and Objectives We propose an automated segmentation pipeline based on deep
learning for proton lung MRI segmentation and ventilation-based quantification which …

Robotic navigation in GPS-denied environments requires case specific approaches for
controlling a mobile robot to any desired destinations. In general, a nominal path is created …

This paper aims at constructing a light-weight object detector that inputs a depth and a color
image from a stereo camera. Specifically, by extending the network architecture of YOLOv3 …

Abstract Machine learning is the state of the art for many recurring tasks in several
heterogeneous domains. In the last decade, it has been also widely used in Precision …

Our perception of our surrounding environment is limited by the constraints of human
biology. The field of augmented perception asks how our sensory capabilities can be …

Object detection and classification is a key task in many computer vision applications such
as smart surveillance and autonomous vehicles. Recent advances in deep learning have …

High throughput and low latency inference of deep neural networks are critical for the
deployment of deep learning applications. This paper presents the efficient inference …

People with Visual Impairments (PVI) experience greater difficulties with daily tasks, such as
supermarket shop**. Identifying and purchasing an item proves challenging for PVI. Using …

Systematic testing of autonomous vehicles operating in complex real-world scenarios is a
difficult and expensive problem. We present Paracosm, a reactive language for writing test …