A Two-Layered Anomaly Detection Technique Based on Multi-modal Flow Behavior Models

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.

This work proposes a decentralized architecture, where individual agents aim at solving a classification problem while observing streaming features of different dimensions and arising from possibly different distributions. In the context of social learning ...

Preserving privacy is a growing concern in our society where cameras are ubiquitous. In this work, we propose a trainable image acquisition method that removes the sensitive information in the optical domain before it reaches the image sensor. The method b ...

Forecasting pedestrians' future motions is essential for autonomous driving systems to safely navigate in urban areas. However, existing prediction algorithms often overly rely on past observed trajectories and tend to fail around abrupt dynamic changes, s ...

Despite the large body of academic work on machine learning security, little is known about the occurrence of attacks on machine learning systems in the wild. In this paper, we report on a quantitative study with 139 industrial practitioners. We analyze at ...

Moving walkways are pedestrian dedicated hardware which generally decrease pedestrian travel time. We propose the utilization of these devices to dynamically control pedestrian flows in order to improve pedestrian dynamics. Three variations of a control st ...

For several decades - and still today - mobility policies in industrialised countries have sought to reduce travel time to meet the expectations of infrastructure users for speed. However, despite major investments to achieve this objective of improving ac ...

Background and objective The automated detection of atrial activations (AAs) recorded from intracardiac electrograms (IEGMs) during atrial fibrillation (AF) is challenging considering their various amplitudes, morphologies and cycle length. Activation time ...

Massive molecular testing for COVID-19 has been pointed out as fundamental to moderate the spread of the pandemic. Pooling methods can enhance testing efficiency, but they are viable only at low incidences of the disease. We propose Smart Pooling, a machin ...

Deep motion forecasting models have achieved great success when trained on a massive amount of data. Yet, they often perform poorly when training data is limited. To address this challenge, we propose a transfer learning approach for efficiently adapting p ...

Signalized intersections are a fundamental part of urban networks. Their understanding is crucial to identify congestion patterns, queues, delays, and safety issues in local and network level. In this work, we analyze multimodal vehicle trajectories and pr ...

Humans have an incredible sense of self-preservation that is both instilled, and also learned through experience. One system which contributes to this is the pain and reflex system which both minimizes damage through involuntary reflex ac- tions and also s ...

In this paper, we propose and compare personalized models for Productive Engagement (PE) recognition. PE is defined as the level of engagement that maximizes learning. Previously, in the context of robot-mediated collaborative learning, a framework of prod ...

A Two-Layered Anomaly Detection Technique Based on Multi-modal Flow Behavior Models

Chat with Graph Search

Learning From Heterogeneous Data Based on Social Interactions Over Graphs

Privacy-Preserving Image Acquisition for Neural Vision Systems

Pedestrian Stop and Go Forecasting with Hybrid Feature Fusion

Machine Learning Security in Industry: A Quantitative Survey

Controlling pedestrian flows with moving walkways

L'usage et l'expérience du temps de déplacement dans la perspective du report modal

Evaluation and optimization of novel extraction algorithms for the automatic detection of atrial activations recorded within the pulmonary veins during atrial fibrillation

Smart pooling: AI-powered COVID-19 informative group testing

Motion Style Transfer: Modular Low-Rank Adaptation for Deep Motion Forecasting

An automatized signal timing detection at signalized intersections with detailed vehicle trajectory data

Bio-inspired Reflex System for Learning Visual Information for Resilient Robotic Manipulation

Personalized Productive Engagement Recognition in Robot-Mediated Collaborative Learning