8 citations · 10 across the 5 of their papers we have counts for
12 papers
Deep Learning Frameworks Applied For Audio-Visual Scene Classification
Lam Pham, Alexander Schindler, Mina Schütz +3
In this paper, we present deep learning frameworks for audio-visual scene classification (SC) and indicate how individual visual and audio features as well as their combination aff…
A Low-Compexity Deep Learning Framework For Acoustic Scene Classification
Lam Pham, Hieu Tang, Anahid Jalali +2
In this paper, we presents a low-complexity deep learning frameworks for acoustic scene classification (ASC). The proposed framework can be separated into three main steps: Front-e…
Multi-Modal Video Forensic Platform for Investigating Post-Terrorist Attack Scenarios
Alexander Schindler, Andrew Lindley, Anahid Jalali +3
The forensic investigation of a terrorist attack poses a significant challenge to the investigative authorities, as often several thousand hours of video footage must be viewed. La…
Unsupervised Cross-Modal Audio Representation Learning from Unstructured Multilingual Text
Alexander Schindler, Sergiu Gordea, Peter Knees
We present an approach to unsupervised audio representation learning. Based on a triplet neural network architecture, we harnesses semantically related cross-modal information to e…
Multi-Modal Music Information Retrieval: Augmenting Audio-Analysis with Visual Computing for Improved Music Video Analysis
Alexander Schindler
This thesis combines audio-analysis with computer vision to approach Music Information Retrieval (MIR) tasks from a multi-modal perspective. This thesis focuses on the information…
Deep Learning for MIR Tutorial
Alexander Schindler, Thomas Lidy, Sebastian Böck
Deep Learning has become state of the art in visual computing and continuously emerges into the Music Information Retrieval (MIR) and audio retrieval domain. In order to bring atte…