Search Results for author:
Found 5 papers, 3 papers with code
New Perspectives on Sensitivity and Identifiability Analysis using the Unscented Kalman Filter
Practically, we present results which show the UKF to be an efficient method for assigning personalised input parameters from experimental data in real-time, which enhances the clinical significance of our approach.
A Systematic Collection of Medical Image Datasets for Deep Learning
Thus, as comprehensive as possible, this paper provides a collection of medical image datasets with their associated challenges for deep learning research.
Damage accumulation during high temperature fatigue of Ti/SiC$_f$ metal matrix composites under different stress amplitudes
The three-dimensional morphology of the crack and fibre fractures has been mapped by CT. During stable growth, matrix cracking dominates with the crack deflecting (by 50-100 $\mu$m in height) when bypassing bridging fibres.
Computed Tomography (CT)
X-Ray Diffraction (XRD)
Materials Science
Applied Physics
Toward Marker-free 3D Pose Estimation in Lifting: A Deep Multi-view Solution
The results are also compared with state-of-the-art methods on HumanEva-I dataset, which demonstrates the superior performance of our approach.
Beam Search for Learning a Deep Convolutional Neural Network of 3D Shapes
Each state of the beam search corresponds to a candidate CNN.
