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20182026
most citedOn Multitask Loss Function for Audio Event Detection and Localization

16 citations · 43 across the 23 of their papers we have counts for

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6 papers · 1 filter

cs.LG2023

A Robust Deep Learning System for Motor Bearing Fault Detection: Leveraging Multiple Learning Strategies and a Novel Double Loss Function

Khoa Tran, Lam Pham, Vy-Rin Nguyen +1

Motor bearing fault detection (MBFD) is critical for maintaining the reliability and operational efficiency of industrial machinery. Early detection of bearing faults can prevent s…

cs.LG2023

Robust-MBDL: A Robust Multi-branch Deep Learning Based Model for Remaining Useful Life Prediction and Operational Condition Identification of Rotating Machines

Khoa Tran, Hai-Canh Vu, Lam Pham +1

In this paper, a Robust Multi-branch Deep learning-based system for remaining useful life (RUL) prediction and condition operations (CO) identification of rotating machines is prop…

cs.LG2021

An Analysis of State-of-the-art Activation Functions For Supervised Deep Neural Network

Anh Nguyen, Khoa Pham, Dat Ngo +2

This paper provides an analysis of state-of-the-art activation functions with respect to supervised classification of deep neural network. These activation functions comprise of Re…

cs.LG2020

Deep Learning Framework Applied for Predicting Anomaly of Respiratory Sounds

Dat Ngo, Lam Pham, Anh Nguyen +3

This paper proposes a robust deep learning framework used for classifying anomaly of respiratory cycles. Initially, our framework starts with front-end feature extraction step. Thi…

cs.LG2020

Improving GANs for Speech Enhancement

Huy Phan, Ian V. McLoughlin, Lam Pham +4

Generative adversarial networks (GAN) have recently been shown to be efficient for speech enhancement. However, most, if not all, existing speech enhancement GANs (SEGAN) make use…

cs.LG2018

Unifying Isolated and Overlapping Audio Event Detection with Multi-Label Multi-Task Convolutional Recurrent Neural Networks

Huy Phan, Oliver Y. Chén, Philipp Koch +4

We propose a multi-label multi-task framework based on a convolutional recurrent neural network to unify detection of isolated and overlapping audio events. The framework leverages…