1.9k citations · 2.6k across the 51 of their papers we have counts for
10 papers · 1 filter
Traversing Latent Space using Decision Ferns
Yan Zuo, Gil Avraham, Tom Drummond
The practice of transforming raw data to a feature space so that inference can be performed in that space has been popular for many years. Recently, rapid progress in deep neural n…
Approximate Fisher Information Matrix to Characterise the Training of Deep Neural Networks
Zhibin Liao, Tom Drummond, Ian Reid +1
In this paper, we introduce a novel methodology for characterising the performance of deep learning networks (ResNets and DenseNet) with respect to training convergence and general…
Real-Time Joint Semantic Segmentation and Depth Estimation Using Asymmetric Annotations
Vladimir Nekrasov, Thanuja Dharmasiri, Andrew Spek +3
Deployment of deep learning models in robotics as sensory information extractors can be a daunting task to handle, even using generic GPU cards. Here, we address three of its most…
CReaM: Condensed Real-time Models for Depth Prediction using Convolutional Neural Networks
Andrew Spek, Thanuja Dharmasiri, Tom Drummond
Since the resurgence of CNNs the robotic vision community has developed a range of algorithms that perform classification, semantic segmentation and structure prediction (depths, n…
ENG: End-to-end Neural Geometry for Robust Depth and Pose Estimation using CNNs
Thanuja Dharmasiri, Andrew Spek, Tom Drummond
Recovering structure and motion parameters given a image pair or a sequence of images is a well studied problem in computer vision. This is often achieved by employing Structure fr…
Quantity beats quality for semantic segmentation of corrosion in images
Will Nash, Tom Drummond, Nick Birbilis
Dataset creation is typically one of the first steps when applying Artificial Intelligence methods to a new task; and the real world performance of models hinges on the quality and…