no code implementations • 20 May 2023 • Xiao-Min Zeng, Yan Song, Zhu Zhuo, Yu Zhou, Yu-Hong Li, Hui Xue, Li-Rong Dai, Ian McLoughlin
In this paper, we propose a joint generative and contrastive representation learning method (GeCo) for anomalous sound detection (ASD).
no code implementations • 7 Mar 2023 • Kang Li, Yan Song, Li-Rong Dai, Ian McLoughlin, Xin Fang, Lin Liu
In this paper, we propose an effective sound event detection (SED) method based on the audio spectrogram transformer (AST) model, pretrained on the large-scale AudioSet for audio tagging (AT) task, termed AST-SED.
no code implementations • 25 Feb 2023 • Lam Pham, Cam Le, Dat Ngo, Anh Nguyen, Jasmin Lampert, Alexander Schindler, Ian McLoughlin
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 remote sensing image.
2 code implementations • 16 Jun 2022 • Zhifu Gao, Shiliang Zhang, Ian McLoughlin, Zhijie Yan
However, due to an independence assumption within the output tokens, performance of single-step NAR is inferior to that of AR models, especially with a large-scale corpus.
no code implementations • 3 Mar 2021 • Huy Phan, Huy Le Nguyen, Oliver Y. Chén, Lam Pham, Philipp Koch, Ian McLoughlin, Alfred Mertins
The learned embedding in the subnetworks are then concatenated to form the multi-view embedding for classification similar to a simple concatenation network.
no code implementations • 26 Dec 2020 • Lam Pham, Huy Phan, Ross King, Alfred Mertins, Ian McLoughlin
This paper presents an inception-based deep neural network for detecting lung diseases using respiratory sound input.
no code implementations • 20 Oct 2020 • Ramaswamy Palaniappan, Surej Mouli, Evangelina Fringi, Howard Bowman, Ian McLoughlin
BrakeAcc results also show that experienced subjects were quicker to respond to the activation of brake lights by releasing the accelerator pedal.
1 code implementation • 18 Oct 2020 • Huy Phan, Huy Le Nguyen, Oliver Y. Chén, Philipp Koch, Ngoc Q. K. Duong, Ian McLoughlin, Alfred Mertins
Existing generative adversarial networks (GANs) for speech enhancement solely rely on the convolution operation, which may obscure temporal dependencies across the sequence input.
no code implementations • 11 Sep 2020 • Huy Phan, Lam Pham, Philipp Koch, Ngoc Q. K. Duong, Ian McLoughlin, Alfred Mertins
Audio event localization and detection (SELD) have been commonly tackled using multitask models.
no code implementations • 4 Apr 2020 • Lam Pham, Huy Phan, Ramaswamy Palaniappan, Alfred Mertins, Ian McLoughlin
This paper presents and explores a robust deep learning framework for auscultation analysis.
no code implementations • 21 Jan 2020 • Lam Pham, Ian McLoughlin, Huy Phan, Minh Tran, Truc Nguyen, Ramaswamy Palaniappan
This paper presents a robust deep learning framework developed to detect respiratory diseases from recordings of respiratory sounds.
no code implementations • 19 Dec 2019 • Xiaoxiao Miao, Ian McLoughlin
This paper presents a novel Dialect Identification (DID) system developed for the Fifth Edition of the Multi-Genre Broadcast challenge, the task of Fine-grained Arabic Dialect Identification (MGB-5 ADI Challenge).
1 code implementation • 30 Jul 2019 • Huy Phan, Oliver Y. Chén, Philipp Koch, Zongqing Lu, Ian McLoughlin, Alfred Mertins, Maarten De Vos
We employ the Montreal Archive of Sleep Studies (MASS) database consisting of 200 subjects as the source domain and study deep transfer learning on three different target domains: the Sleep Cassette subset and the Sleep Telemetry subset of the Sleep-EDF Expanded database, and the Surrey-cEEGrid database.
Ranked #1 on Multimodal Sleep Stage Detection on Surrey-PSG
Automatic Sleep Stage Classification Multimodal Sleep Stage Detection +2
no code implementations • 6 Apr 2019 • Huy Phan, Oliver Y. Chén, Lam Pham, Philipp Koch, Maarten De Vos, Ian McLoughlin, Alfred Mertins
Acoustic scenes are rich and redundant in their content.
no code implementations • 2 Nov 2018 • Huy Phan, Oliver Y. Chén, Philipp Koch, Lam Pham, Ian McLoughlin, Alfred Mertins, Maarten De Vos
We propose a multi-label multi-task framework based on a convolutional recurrent neural network to unify detection of isolated and overlapping audio events.
no code implementations • 2 Nov 2018 • Huy Phan, Oliver Y. Chén, Philipp Koch, Lam Pham, Ian McLoughlin, Alfred Mertins, Maarten De Vos
Moreover, as model fusion with deep network ensemble is prevalent in audio scene classification, we further study whether, and if so, when model fusion is necessary for this task.
no code implementations • 6 Dec 2017 • Huy Phan, Philipp Koch, Ian McLoughlin, Alfred Mertins
The proposed system consists of a novel inference step coupled with dual parallel tailored-loss deep neural networks (DNNs).
no code implementations • 29 Apr 2016 • Huy Phan, Marco Maass, Lars Hertel, Radoslaw Mazur, Ian McLoughlin, Alfred Mertins
The entries of the descriptor are produced by evaluating a set of regressors on the input signal.