26 citations · 100 across the 18 of their papers we have counts for
8 papers · 1 filter
Selective manipulation of disentangled representations for privacy-aware facial image processing
Sander De Coninck, Wei-Cheng Wang, Sam Leroux +1
Camera sensors are increasingly being combined with machine learning to perform various tasks such as intelligent surveillance. Due to its computational complexity, most of these m…
Privacy Aware Person Detection in Surveillance Data
Sander De Coninck, Sam Leroux, Pieter Simoens
Crowd management relies on inspection of surveillance video either by operators or by object detection models. These models are large, making it difficult to deploy them on resourc…
Intelligent Frame Selection as a Privacy-Friendlier Alternative to Face Recognition
Mattijs Baert, Sam Leroux, Pieter Simoens
The widespread deployment of surveillance cameras for facial recognition gives rise to many privacy concerns. This study proposes a privacy-friendly alternative to large scale faci…
Decoupled Appearance and Motion Learning for Efficient Anomaly Detection in Surveillance Video
Bo Li, Sam Leroux, Pieter Simoens
Automating the analysis of surveillance video footage is of great interest when urban environments or industrial sites are monitored by a large number of cameras. As anomalies are…
Visualizing Convolutional Neural Networks to Improve Decision Support for Skin Lesion Classification
Pieter Van Molle, Miguel De Strooper, Tim Verbelen +3
Because of their state-of-the-art performance in computer vision, CNNs are becoming increasingly popular in a variety of fields, including medicine. However, as neural networks are…
Learning to Grasp from a Single Demonstration
Pieter Van Molle, Tim Verbelen, Elias De Coninck +3
Learning-based approaches for robotic grasping using visual sensors typically require collecting a large size dataset, either manually labeled or by many trial and errors of a robo…
IamNN: Iterative and Adaptive Mobile Neural Network for Efficient Image Classification
Sam Leroux, Pavlo Molchanov, Pieter Simoens +3
Deep residual networks (ResNets) made a recent breakthrough in deep learning. The core idea of ResNets is to have shortcut connections between layers that allow the network to be m…
Lazy Evaluation of Convolutional Filters
Sam Leroux, Steven Bohez, Cedric De Boom +5
In this paper we propose a technique which avoids the evaluation of certain convolutional filters in a deep neural network. This allows to trade-off the accuracy of a deep neural n…