3 papers
cs.CV2024
From CNN to CNN + RNN: Adapting Visualization Techniques for Time-Series Anomaly Detection
Fabien Poirier
Deep neural networks are highly effective in solving complex problems but are often viewed as "black boxes," limiting their adoption in contexts where transparency and explainabili…
cs.CV2024
Real-Time Anomaly Detection in Video Streams
Fabien Poirier
This thesis is part of a CIFRE agreement between the company Othello and the LIASD laboratory. The objective is to develop an artificial intelligence system that can detect real-ti…
cs.CV2024
Hybrid Architecture for Real-Time Video Anomaly Detection: Integrating Spatial and Temporal Analysis
Fabien Poirier
In this paper, we propose a new architecture for real-time anomaly detection in video data, inspired by human behavior combining spatial and temporal analyses. This approach uses t…