40 citations · 107 across the 14 of their papers we have counts for
8 papers · 1 filter
Spike Encoding for Environmental Sound: A Comparative Benchmark
Andres Larroza, Javier Naranjo-Alcazar, Vicent Ortiz +2
Spiking Neural Networks (SNNs) offer energy efficient processing suitable for edge applications, but conventional sensor data must first be converted into spike trains for neuromor…
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…
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…
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…
Acoustic Scene Classification with Squeeze-Excitation Residual Networks
Javier Naranjo-Alcazar, Sergi Perez-Castanos, Pedro Zuccarello +1
Acoustic scene classification (ASC) is a problem related to the field of machine listening whose objective is to classify/tag an audio clip in a predefined label describing a scene…
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…
On the performance of residual block design alternatives in convolutional neural networks for end-to-end audio classification
Javier Naranjo-Alcazar, Sergi Perez-Castanos, Irene Martin-Morato +2
Residual learning is a recently proposed learning framework to facilitate the training of very deep neural networks. Residual blocks or units are made of a set of stacked layers, w…
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…