10 citations · 10 across the 2 of their papers we have counts for
8 papers
VI-Net: View-Invariant Quality of Human Movement Assessment
Faegheh Sardari, Adeline Paiement, Sion Hannuna +1
We propose a view-invariant method towards the assessment of the quality of human movements which does not rely on skeleton data. Our end-to-end convolutional neural network consis…
Towards automated mobile-phone-based plant pathology management
Nantheera Anantrasirichai, Sion Hannuna, Nishan Canagarajah
This paper presents a framework which uses computer vision algorithms to standardise images and analyse them for identifying crop diseases automatically. The tools are created to b…
CaloriNet: From silhouettes to calorie estimation in private environments
Alessandro Masullo, Tilo Burghardt, Dima Damen +3
We propose a novel deep fusion architecture, CaloriNet, for the online estimation of energy expenditure for free living monitoring in private environments, where RGB data is discar…
Semantically Selective Augmentation for Deep Compact Person Re-Identification
Víctor Ponce-López, Tilo Burghardt, Sion Hannunna +3
We present a deep person re-identification approach that combines semantically selective, deep data augmentation with clustering-based network compression to generate high performa…
A Guide to the SPHERE 100 Homes Study Dataset
Atis Elsts, Tilo Burghardt, Dallan Byrne +18
The SPHERE project has developed a multi-modal sensor platform for health and behavior monitoring in residential environments. So far, the SPHERE platform has been deployed for dat…
Automatic Leaf Extraction from Outdoor Images
N. Anantrasirichai, Sion Hannuna, Nishan Canagarajah
Automatic plant recognition and disease analysis may be streamlined by an image of a complete, isolated leaf as an initial input. Segmenting leaves from natural images is a hard pr…