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09/16/2023
Regularized Contrastive Pre-training for Few-shot Bioacoustic Sound Detection
Bioacoustic sound event detection allows for better understanding of ani...
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09/02/2023
Pretraining Representations for Bioacoustic Few-shot Detection using Supervised Contrastive Learning
Deep learning has been widely used recently for sound event detection an...
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10/27/2022
Supervised Contrastive Learning for Respiratory Sound Classification
Automatic respiratory sound classification using machine learning is a c...
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08/18/2022
Learning-based estimation of in-situ wind speed from underwater acoustics
Wind speed retrieval at sea surface is of primary importance for scienti...
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03/09/2022
Pruning Graph Convolutional Networks to select meaningful graph frequencies for fMRI decoding
Graph Signal Processing is a promising framework to manipulate brain sig...
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08/23/2021
Graph-LDA: Graph Structure Priors to Improve the Accuracy in Few-Shot Classification
It is very common to face classification problems where the number of av...
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10/23/2020
Few-shot Learning for Decoding Brain Signals
Few-shot learning consists in addressing data-thrifty (inductive few-sho...
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11/18/2019
Efficient Hardware Implementation of Incremental Learning and Inference on Chip
In this paper, we tackle the problem of incrementally learning a classif...
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10/11/2019
Spectral Graph Wavelet Transform as Feature Extractor for Machine Learning in Neuroimaging
Graph Signal Processing has become a very useful framework for signal op...
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08/19/2019
Comparing linear structure-based and data-driven latent spatial representations for sequence prediction
Predicting the future of Graph-supported Time Series (GTS) is a key chal...
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12/29/2018
Quantized Guided Pruning for Efficient Hardware Implementations of Convolutional Neural Networks
Convolutional Neural Networks (CNNs) are state-of-the-art in numerous co...
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10/04/2018
Transfer Incremental Learning using Data Augmentation
Deep learning-based methods have reached state of the art performances, ...
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03/06/2017