← Search

Christos Garoufis

6 accepted papers

2025

Power in Unity: Combining in-Domain and out-of-Domain Pre-Training Strategies for EEG-Based Person Identification

ICASSP 2025accepted

We present the NTUA-IRAL team’s solution for the Person Identification track of the Signal Processing EEG-Music Emotion Recognition Grand Challenge, hosted at ICASSP. Our approach employs an ensemble of three CNNs, each pretrained using a distinct strategy: contrastive pre-training, traditional Imag…

Cited by 0SourceScholar
2023

E-Prevention: The ICASSP-2023 Challenge on Person Identification and Relapse Detection from Continuous Recordings of Biosignals

ICASSP 2023accepted

The e-Prevention challenge concerns the analysis and processing of long-term continuous recordings of biosignals recorded from wearable sensors, i.e., accelerometers, gyroscopes and heart rate monitors embedded in smartwatches, as well as sleep information and daily step count, in order to extract h…

Cited by 0SourceScholar
2023

Relapse Prediction from Long-Term Wearable Data Using Self-Supervised Learning and Survival Analysis

ICASSP 2023accepted

The introduction of biometric signal analysis in psychiatry could potentially reshape the field by making it more accurate, proactive and personalized. Such biosignals usually acquired from wearables encompass the quantification of human behavior and traits. In this study, we use long-term data acqu…

Cited by 0SourceScholar
2022

Enhancing Affective Representations Of Music-Induced Eeg Through Multimodal Supervision And Latent Domain Adaptation

ICASSP 2022accepted

The study of Music Cognition and neural responses to music has been invaluable in understanding human emotions. Brain signals, though, manifest a highly complex structure that makes processing and retrieving meaningful features challenging, particularly of abstract constructs like affect. Moreover,…

Cited by 0SourceScholar
2021

Deep Convolutional and Recurrent Networks for Polyphonic Instrument Classification from Monophonic Raw Audio Waveforms

ICASSP 2021accepted

Sound Event Detection and Audio Classification tasks are traditionally addressed through time-frequency representations of audio signals such as spectrograms. However, the emergence of deep neural networks as efficient feature extractors has enabled the direct use of audio signals for classification…

Cited by 0SourceScholar
2020

An LSTM-Based Dynamic Chord Progression Generation System for Interactive Music Performance

ICASSP 2020accepted

In this paper, we describe an interactive generative music system, designed to handle polyphonic guitar music. We formulate the problem of chord progression generation as a prediction problem. Thus, we propose utilization of an LSTM-based network architecture incorporating neural attention that is a…

Cited by 0SourceScholar