Acoustic scene classification: a comprehensive survey
Acoustic scene classification (ASC) has gained significant interest recently due to its diverse
applications. Various audio signal processing and machine learning methods have been …
applications. Various audio signal processing and machine learning methods have been …
CNN-MoE based framework for classification of respiratory anomalies and lung disease detection
This paper presents and explores a robust deep learning framework for auscultation
analysis. This aims to classify anomalies in respiratory cycles and detect diseases, from …
analysis. This aims to classify anomalies in respiratory cycles and detect diseases, from …
An analysis of state-of-the-art activation functions for supervised deep neural network
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 …
supervised classification of deep neural network. These activation functions comprise of …
Low-Complexity Acoustic Scene Classification Using Data Augmentation and Lightweight ResNet
We present a work on low-complexity acoustic scene classification (ASC) with multiple
devices, namely the subtask A of Task 1 of the DCASE2021 challenge. This subtask focuses …
devices, namely the subtask A of Task 1 of the DCASE2021 challenge. This subtask focuses …
Robust, general, and low complexity acoustic scene classification systems and an effective visualization for presenting a sound scene context
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 …
the task of identifying the scene of an audio recording from its acoustic signature. In …
Deep learning frameworks applied for audio-visual scene classification
In this paper, we present deep learning frameworks for audio-visual scene classification
(SC) and indicate how individual visual, audio features as well as their combination affect …
(SC) and indicate how individual visual, audio features as well as their combination affect …
An unsupervised machine learning approach for ground‐motion spectra clustering and selection
Clustering analysis of sequence data continues to address many applications in
engineering design, aided with the rapid growth of machine learning in applied science …
engineering design, aided with the rapid growth of machine learning in applied science …
Hierarchical classification based on coarse-to fine-grained knowledge transfer
Z Qiu, M Hu, H Zhao - International Journal of Approximate Reasoning, 2022 - Elsevier
Hierarchical classification has become one of the most popular research topics because the
scale of data has increased exponentially. Top-down hierarchical classification is an …
scale of data has increased exponentially. Top-down hierarchical classification is an …
An audio-visual dataset and deep learning frameworks for crowded scene classification
In this paper, we present the task of audio-visual scene classification (SC) where input
videos are classified into one of five real-life crowded scenes:'Riot','Noise-Street','Firework …
videos are classified into one of five real-life crowded scenes:'Riot','Noise-Street','Firework …
Domestic activities classification from audio recordings using multi-scale dilated depthwise separable convolutional network
Y Zeng, Y Li, Z Zhou, R Wang… - 2021 IEEE 23rd …, 2021 - ieeexplore.ieee.org
Domestic activities classification (DAC) from audio recordings aims at classifying audio
recordings into predefined categories of domestic activities, which is an effective way for …
recordings into predefined categories of domestic activities, which is an effective way for …