Search Results for author: Sam Leroux

Found 14 papers, 2 papers with code

Selective manipulation of disentangled representations for privacy-aware facial image processing

no code implementations26 Aug 2022 Sander De Coninck, Wei-Cheng Wang, Sam Leroux, Pieter Simoens

Camera sensors are increasingly being combined with machine learning to perform various tasks such as intelligent surveillance.

Image Manipulation

Audio-guided Album Cover Art Generation with Genetic Algorithms

no code implementations14 Jul 2022 James Marien, Sam Leroux, Bart Dhoedt, Cedric De Boom

We find that our framework can generate suitable cover art for most genres, and that the visual features adapt themselves to audio feature changes.

TinyMLOps: Operational Challenges for Widespread Edge AI Adoption

no code implementations21 Mar 2022 Sam Leroux, Pieter Simoens, Meelis Lootus, Kartik Thakore, Akshay Sharma

Deploying machine learning applications on edge devices can bring clear benefits such as improved reliability, latency and privacy but it also introduces its own set of challenges.

Privacy Aware Person Detection in Surveillance Data

no code implementations28 Oct 2021 Sander De Coninck, Sam Leroux, Pieter Simoens

Crowd management relies on inspection of surveillance video either by operators or by object detection models.

Face Recognition Human Detection +3

Multi-branch Neural Networks for Video Anomaly Detection in Adverse Lighting and Weather Conditions

no code implementations WACV 2021 Sam Leroux, Bo Li, Pieter Simoens

Automated anomaly detection in surveillance videos has attracted much interest as it provides a scalable alternative to manual monitoring.

Anomaly Detection In Surveillance Videos

Intelligent Frame Selection as a Privacy-Friendlier Alternative to Face Recognition

no code implementations19 Jan 2021 Mattijs Baert, Sam Leroux, Pieter Simoens

For this, we train a variational autoencoder on high quality face images from a publicly available dataset and use the reconstruction probability as a metric to estimate the quality of each face crop.

Face Recognition Face Verification +1

Decoupled Appearance and Motion Learning for Efficient Anomaly Detection in Surveillance Video

1 code implementation10 Nov 2020 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.

Anomaly Detection

Improving Generalization for Abstract Reasoning Tasks Using Disentangled Feature Representations

no code implementations12 Nov 2018 Xander Steenbrugge, Sam Leroux, Tim Verbelen, Bart Dhoedt

In this work we explore the generalization characteristics of unsupervised representation learning by leveraging disentangled VAE's to learn a useful latent space on a set of relational reasoning problems derived from Raven Progressive Matrices.

Relational Reasoning Representation Learning

Privacy Aware Offloading of Deep Neural Networks

no code implementations30 May 2018 Sam Leroux, Tim Verbelen, Pieter Simoens, Bart Dhoedt

Deep neural networks require large amounts of resources which makes them hard to use on resource constrained devices such as Internet-of-things devices.

Transfer Learning with Binary Neural Networks

no code implementations29 Nov 2017 Sam Leroux, Steven Bohez, Tim Verbelen, Bert Vankeirsbilck, Pieter Simoens, Bart Dhoedt

Binary neural networks are attractive in this case because the logical operations are very fast and efficient when implemented in hardware.

Transfer Learning

Decoupled Learning of Environment Characteristics for Safe Exploration

no code implementations9 Aug 2017 Pieter Van Molle, Tim Verbelen, Steven Bohez, Sam Leroux, Pieter Simoens, Bart Dhoedt

However, when learning a task using reinforcement learning, the agent cannot distinguish the characteristics of the environment from those of the task.

reinforcement-learning Safe Exploration

Lazy Evaluation of Convolutional Filters

no code implementations27 May 2016 Sam Leroux, Steven Bohez, Cedric De Boom, Elias De Coninck, Tim Verbelen, Bert Vankeirsbilck, Pieter Simoens, Bart Dhoedt

In this paper we propose a technique which avoids the evaluation of certain convolutional filters in a deep neural network.

Efficiency Evaluation of Character-level RNN Training Schedules

1 code implementation9 May 2016 Cedric De Boom, Sam Leroux, Steven Bohez, Pieter Simoens, Thomas Demeester, Bart Dhoedt

We present four training and prediction schedules from the same character-level recurrent neural network.

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