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20192025
most citedCNN depth analysis with different channel inputs for Acoustic Scene Classification

5 citations · 12 across the 7 of their papers we have counts for

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cs.SD2021★ 1 cited

Task 1A DCASE 2021: Acoustic Scene Classification with mismatch-devices using squeeze-excitation technique and low-complexity constraint

Javier Naranjo-Alcazar, Sergi Perez-Castanos, Maximo Cobos +2

Acoustic scene classification (ASC) is one of the most popular problems in the field of machine listening. The objective of this problem is to classify an audio clip into one of th…

cs.SD2021

TASK3 DCASE2021 Challenge: Sound event localization and detection using squeeze-excitation residual CNNs

Javier Naranjo-Alcazar, Sergi Perez-Castanos, Pedro Zuccarello +2

Sound event localisation and detection (SELD) is a problem in the field of automatic listening that aims at the temporal detection and localisation (direction of arrival estimation…

cs.SD2020★ 2 cited

Sound Event Localization and Detection using Squeeze-Excitation Residual CNNs

Javier Naranjo-Alcazar, Sergi Perez-Castanos, Jose Ferrandis +2

Sound Event Localization and Detection (SELD) is a problem related to the field of machine listening whose objective is to recognize individual sound events, detect their temporal…

cs.SD2020★ 1 cited

An Open-set Recognition and Few-Shot Learning Dataset for Audio Event Classification in Domestic Environments

Javier Naranjo-Alcazar, Sergi Perez-Castanos, Pedro Zuccarrello +4

The problem of training with a small set of positive samples is known as few-shot learning (FSL). It is widely known that traditional deep learning (DL) algorithms usually show ver…

cs.SD2019★ 5 cited

CNN depth analysis with different channel inputs for Acoustic Scene Classification

Sergi Perez-Castanos, Javier Naranjo-Alcazar, Pedro Zuccarello +2

Acoustic scene classification (ASC) has been approached in the last years using deep learning techniques such as convolutional neural networks or recurrent neural networks. Many st…