13 citations · 47 across the 21 of their papers we have counts for
22 papers
Low-complexity deep learning frameworks for acoustic scene classification using teacher-student scheme and multiple spectrograms
Lam Pham, Dat Ngo, Cam Le +2
In this technical report, a low-complexity deep learning system for acoustic scene classification (ASC) is presented. The proposed system comprises two main phases: (Phase I) Train…
Deep Learning Based Multimodal with Two-phase Training Strategy for Daily Life Video Classification
Lam Pham, Trang Le, Cam Le +3
In this paper, we present a deep learning based multimodal system for classifying daily life videos. To train the system, we propose a two-phase training strategy. In the first tra…
A Light-weight Deep Learning Model for Remote Sensing Image Classification
Lam Pham, Cam Le, Dat Ngo +4
In this paper, we present a high-performance and light-weight deep learning model for Remote Sensing Image Classification (RSIC), the task of identifying the aerial scene of a remo…
Robust, General, and Low Complexity Acoustic Scene Classification Systems and An Effective Visualization for Presenting a Sound Scene Context
Lam Pham, Dusan Salovic, Anahid Jalali +4
In this paper, we present a comprehensive analysis of Acoustic Scene Classification (ASC), the task of identifying the scene of an audio recording from its acoustic signature. In p…
Remote Sensing Image Classification using Transfer Learning and Attention Based Deep Neural Network
Lam Pham, Khoa Tran, Dat Ngo +2
The task of remote sensing image scene classification (RSISC), which aims at classifying remote sensing images into groups of semantic categories based on their contents, has taken…
Low-complexity deep learning frameworks for acoustic scene classification
Lam Pham, Dat Ngo, Anahid Jalali +1
In this report, we presents low-complexity deep learning frameworks for acoustic scene classification (ASC). The proposed frameworks can be separated into four main steps: Front-en…
Wider or Deeper Neural Network Architecture for Acoustic Scene Classification with Mismatched Recording Devices
Lam Pham, Khoa Dinh, Dat Ngo +2
In this paper, we present a robust and low complexity system for Acoustic Scene Classification (ASC), the task of identifying the scene of an audio recording. We first construct an…
An Ensemble of Deep Learning Frameworks Applied For Predicting Respiratory Anomalies
Lam Pham, Dat Ngo, Truong Hoang +2
In this paper, we evaluate various deep learning frameworks for detecting respiratory anomalies from input audio recordings. To this end, we firstly transform audio respiratory cyc…
An Audio-Visual Dataset and Deep Learning Frameworks for Crowded Scene Classification
Lam Pham, Dat Ngo, Phu X. Nguyen +2
This paper presents a task of audio-visual scene classification (SC) where input videos are classified into one of five real-life crowded scenes: 'Riot', 'Noise-Street', 'Firework-…
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…
Automatic Sexism Detection with Multilingual Transformer Models
Mina Schütz, Jaqueline Boeck, Daria Liakhovets +7
Sexism has become an increasingly major problem on social networks during the last years. The first shared task on sEXism Identification in Social neTworks (EXIST) at IberLEF 2021…
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…
Multi-Task Music Representation Learning from Multi-Label Embeddings
Alexander Schindler, Peter Knees
This paper presents a novel approach to music representation learning. Triplet loss based networks have become popular for representation learning in various multimedia retrieval d…
Predicting Time-to-Failure of Plasma Etching Equipment using Machine Learning
Anahid Jalali, Clemens Heistracher, Alexander Schindler +5
Predicting unscheduled breakdowns of plasma etching equipment can reduce maintenance costs and production losses in the semiconductor industry. However, plasma etching is a complex…
Large Scale Audio-Visual Video Analytics Platform for Forensic Investigations of Terroristic Attacks
Alexander Schindler, Martin Boyer, Andrew Lindley +2
The forensic investigation of a terrorist attack poses a huge challenge to the investigative authorities, as several thousand hours of video footage need to be spotted. To assist l…
A Multi-modal Deep Neural Network approach to Bird-song identification
Botond Fazeka, Alexander Schindler, Thomas Lidy +1
We present a multi-modal Deep Neural Network (DNN) approach for bird song identification. The presented approach takes both audio samples and metadata as input. The audio is fed in…
Multi-Temporal Resolution Convolutional Neural Networks for Acoustic Scene Classification
Alexander Schindler, Thomas Lidy, Andreas Rauber
In this paper we present a Deep Neural Network architecture for the task of acoustic scene classification which harnesses information from increasing temporal resolutions of Mel-Sp…
Fashion and Apparel Classification using Convolutional Neural Networks
Alexander Schindler, Thomas Lidy, Stephan Karner +1
We present an empirical study of applying deep Convolutional Neural Networks (CNN) to the task of fashion and apparel image classification to improve meta-data enrichment of e-comm…