activity
20162026
most citedAugmentation Methods on Monophonic Audio for Instrument Classification in Polyphonic Music

32 citations · 72 across the 16 of their papers we have counts for

collaborators

16 papers

cs.CV2026

NTIRE 2026 Challenge on Video Saliency Prediction: Methods and Results

Andrey Moskalenko, Alexey Bryncev, Ivan Kosmynin +40

This paper presents an overview of the NTIRE 2026 Challenge on Video Saliency Prediction. The goal of the challenge participants was to develop automatic saliency map prediction me…

eess.SP2025★ 1 cited

Teager-Kaiser Energy Methods For EEG Feature Extraction In Biomedical Applications

Ioanna Chourdaki, Kleanthis Avramidis, Christos Garoufis +2

Electroencephalography (EEG) signals are inherently non-linear, non-stationary, and vulnerable to noise sources, making the extraction of discriminative features a long-standing ch…

eess.AS2025

CVSM: Contrastive Vocal Similarity Modeling

Christos Garoufis, Athanasia Zlatintsi, Petros Maragos

The availability of large, unlabeled datasets across various domains has contributed to the development of a plethora of methods that learn representations for multiple target (dow…

eess.AS2025

Classical Guitar Duet Separation using GuitarDuets -- a Dataset of Real and Synthesized Guitar Recordings

Marios Glytsos, Christos Garoufis, Athanasia Zlatintsi +1

Recent advancements in music source separation (MSS) have focused in the multi-timbral case, with existing architectures tailored for the separation of distinct instruments, overlo…

eess.AS2023

Pre-training Music Classification Models via Music Source Separation

Christos Garoufis, Athanasia Zlatintsi, Petros Maragos

In this paper, we study whether music source separation can be used as a pre-training strategy for music representation learning, targeted at music classification tasks. To this en…

eess.AS2023

Multi-Source Contrastive Learning from Musical Audio

Christos Garoufis, Athanasia Zlatintsi, Petros Maragos

Contrastive learning constitutes an emerging branch of self-supervised learning that leverages large amounts of unlabeled data, by learning a latent space, where pairs of different…

cs.SD2022★ 1 cited

Enhancing Affective Representations of Music-Induced EEG through Multimodal Supervision and latent Domain Adaptation

Kleanthis Avramidis, Christos Garoufis, Athanasia Zlatintsi +1

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 make…

eess.AS2021

HTMD-Net: A Hybrid Masking-Denoising Approach to Time-Domain Monaural Singing Voice Separation

Christos Garoufis, Athanasia Zlatintsi, Petros Maragos

The advent of deep learning has led to the prevalence of deep neural network architectures for monaural music source separation, with end-to-end approaches that operate directly on…

cs.SD2021★ 1 cited

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

Kleanthis Avramidis, Agelos Kratimenos, Christos Garoufis +2

Sound Event Detection and Audio Classification tasks are traditionally addressed through time-frequency representations of audio signals such as spectrograms. However, the emergenc…

cs.CY2020★ 4 cited

Identifying differences in physical activity and autonomic function patterns between psychotic patients and controls over a long period of continuous monitoring using wearable sensors

Panagiotis P. Filntisis, Athanasia Zlatintsi, Niki Efthymiou +5

Digital phenotyping is a nascent multidisciplinary field that has the potential to revolutionize psychiatry and its clinical practice. In this paper, we present a rigorous statisti…

eess.SP2020★ 21 cited

Multiscale Fractal Analysis on EEG Signals for Music-Induced Emotion Recognition

Kleanthis Avramidis, Athanasia Zlatintsi, Christos Garoufis +1

Emotion Recognition from EEG signals has long been researched as it can assist numerous medical and rehabilitative applications. However, their complex and noisy structure has prov…

cs.LG2019★ 32 cited

Augmentation Methods on Monophonic Audio for Instrument Classification in Polyphonic Music

Agelos Kratimenos, Kleanthis Avramidis, Christos Garoufis +2

Instrument classification is one of the fields in Music Information Retrieval (MIR) that has attracted a lot of research interest. However, the majority of that is dealing with mon…

cs.CV2019

Deeply Supervised Multimodal Attentional Translation Embeddings for Visual Relationship Detection

Nikolaos Gkanatsios, Vassilis Pitsikalis, Petros Koutras +2

Detecting visual relationships, i.e. <Subject, Predicate, Object> triplets, is a challenging Scene Understanding task approached in the past via linguistic priors or spatial inform…

cs.CV2017★ 11 cited

Multimodal Visual Concept Learning with Weakly Supervised Techniques

Giorgos Bouritsas, Petros Koutras, Athanasia Zlatintsi +1

Despite the availability of a huge amount of video data accompanied by descriptive texts, it is not always easy to exploit the information contained in natural language in order to…

cs.MM2017★ 1 cited

Multimodal Signal Processing and Learning Aspects of Human-Robot Interaction for an Assistive Bathing Robot

A. Zlatintsi, I. Rodomagoulakis, P. Koutras +4

We explore new aspects of assistive living on smart human-robot interaction (HRI) that involve automatic recognition and online validation of speech and gestures in a natural inter…

cs.IR2016

Audio-based Distributional Semantic Models for Music Auto-tagging and Similarity Measurement

Giannis Karamanolakis, Elias Iosif, Athanasia Zlatintsi +2

The recent development of Audio-based Distributional Semantic Models (ADSMs) enables the computation of audio and lexical vector representations in a joint acoustic-semantic space.…