Discriminatively Trained Autoencoders for Fast and Accurate Face Recognition. - Paraskevi Nousi; Anastasios Tefas (EANN, 2017)

Lightweight two-stream convolutional face detection. - Danai Triantafyllidou; Paraskevi Nousi; Anastasios Tefas (EUSIPCO, 2017)

Deep learning algorithms for discriminant autoencoding. - Paraskevi Nousi; Anastasios Tefas (Neurocomputing, 2017)

Convolutional Neural Networks for Visual Information Analysis with Limited Computing Resources. - Paraskevi Nousi; Emmanouil Patsiouras; Anastasios Tefas; Ioannis Pitas (ICIP, 2018)

Fast Deep Convolutional Face Detection in the Wild Exploiting Hard Sample Mining. - Danai Triantafyllidou; Paraskevi Nousi; Anastasios Tefas (Big Data Res., 2018)

Machine Learning for Forecasting Mid Price Movement using Limit Order Book Data. - Paraskevi Nousi; Avraam Tsantekidis; Nikolaos Passalis; Adamantios Ntakaris; Juho Kanniainen; Anastasios Tefas; Moncef Gabbouj; Alexandros Iosifidis (CoRR, 2018)

Deep Convolutional Feature Histograms for Visual Object Tracking. - Paraskevi Nousi; Anastasios Tefas; Ioannis Pitas (ICASSP, 2019)

Joint Lightweight Object Tracking and Detection for Unmanned Vehicles. - Paraskevi Nousi; Danai Triantafyllidou; Anastasios Tefas; Ioannis Pitas (ICIP, 2019)

Embedded UAV Real-Time Visual Object Detection and Tracking. - Paraskevi Nousi; Ioannis Mademlis; Iason Karakostas; Anastasios Tefas; Ioannis Pitas (RCAR, 2019)

Machine Learning for Forecasting Mid-Price Movements Using Limit Order Book Data. - Paraskevi Nousi; Avraam Tsantekidis; Nikolaos Passalis; Adamantios Ntakaris; Juho Kanniainen; Anastasios Tefas; Moncef Gabbouj; Alexandros Iosifidis (IEEE Access, 2019)

Visual Object Detection For Autonomous UAV Cinematography. - Fotini Patrona; Paraskevi Nousi; Ioannis Mademlis; Anastasios Tefas; Ioannis Pitas (NLDL, 2020)

Self-supervised autoencoders for clustering and classification. - Paraskevi Nousi; Anastasios Tefas (Evol. Syst., 2020)

Dense convolutional feature histograms for robust visual object tracking. - Paraskevi Nousi; Anastasios Tefas; Ioannis Pitas (Image Vis. Comput., 2020)

Deep autoencoders for attribute preserving face de-identification. - Paraskevi Nousi; Sotirios Papadopoulos; Anastasios Tefas; Ioannis Pitas (Signal Process. Image Commun., 2020)

Re-identification framework for long term visual object tracking based on object detection and classification. - Paraskevi Nousi; Danai Triantafyllidou; Anastasios Tefas; Ioannis Pitas (Signal Process. Image Commun., 2020)

Efficient Realistic Data Generation Framework Leveraging Deep Learning-Based Human Digitization. - Charalampos Symeonidis; Paraskevi Nousi; Pavlos Tosidis; Konstantinos Tsampazis; Nikolaos Passalis; Anastasios Tefas; Nikos Nikolaidis 001 (EANN, 2021)

Supervised and unsupervised deep learning methodologies - Paraskevi Nousi (2021)

OpenDR: An Open Toolkit for Enabling High Performance, Low Footprint Deep Learning for Robotics. - Nikolaos Passalis; S. Pedrazzi; Robert Babuska; Wolfram Burgard; D. Dias; F. Ferro; Moncef Gabbouj; O. Green; Alexandros Iosifidis; Erdal Kayacan; Jens Kober; O. Michel; et al. (IROS, 2022)

MLGWSC-1: The first Machine Learning Gravitational-Wave Search Mock Data Challenge. - Marlin B. Schäfer; Ondrej Zelenka; Alexander H. Nitz; He Wang 018; Shichao Wu; Zong-Kuan Guo; Zhoujian Cao; Zhixiang Ren; Paraskevi Nousi; Nikolaos Stergioulas; Panagiotis Iosif; Alexandra E. Koloniari; et al. (CoRR, 2022)

A Novel Dataset for Evaluating and Alleviating Domain Shift for Human Detection in Agricultural Fields. - Paraskevi Nousi; Emmanouil Mpampis; Nikolaos Passalis; Ole Green; Anastasios Tefas (CoRR, 2022)

Autoencoder-driven spiral representation learning for gravitational wave surrogate modelling. - Paraskevi Nousi; Styliani-Christina Fragkouli; Nikolaos Passalis; Panagiotis Iosif; Theocharis Apostolatos; George Pappas; Nikolaos Stergioulas; Anastasios Tefas (Neurocomputing, 2022)

Cryptosentiment: A Dataset and Baseline for Sentiment-Aware Deep Reinforcement Learning for Financial Trading. - Loukia Avramelou; Paraskevi Nousi; Nikolaos Passalis; Stavros Doropoulos; Anastasios Tefas (ICASSP Workshops, 2023)

Improving Electric Load Demand Forecasting with Anchor-Based Forecasting Method. - Maria Tzelepi; Paraskevi Nousi; Anastasios Tefas (ICASSP, 2023)

A Sharpe Ratio Based Reward Scheme in Deep Reinforcement Learning for Financial Trading. - Georgios Rodinos; Paraskevi Nousi; Nikolaos Passalis; Anastasios Tefas (AIAI (1), 2023)

Anchored Input-Output Learning for Electrical Load Demand Forecasting. - Paraskevi Nousi; Maria Tzelepi; Anastasios Tefas (ISCAS, 2023)

Variational Voxel Pseudo Image Tracking. - Illia Oleksiienko; Paraskevi Nousi; Nikolaos Passalis; Anastasios Tefas; Alexandros Iosifidis (SSCI, 2023)

Deep Learning for Energy Time-Series Analysis and Forecasting. - Maria Tzelepi; Charalampos Symeonidis; Paraskevi Nousi; Efstratios Kakaletsis; Theodoros Manousis; Pavlos Tosidis; Nikos Nikolaidis 001; Anastasios Tefas (CoRR, 2023)

Leveraging Deep Learning and Online Source Sentiment for Financial Portfolio Management. - Paraskevi Nousi; Loukia Avramelou; Georgios Rodinos; Maria Tzelepi; Theodoros Manousis; Konstantinos Tsampazis; Kyriakos Stefanidis; Dimitris Spanos; Emmanouil Kirtas; Pavlos Tosidis; Avraam Tsantekidis; Nikolaos Passalis; et al. (CoRR, 2023)

Deep residual error and bag-of-tricks learning for gravitational wave surrogate modeling. - Styliani-Christina Fragkouli; Paraskevi Nousi; Nikolaos Passalis; Panagiotis Iosif; Nikolaos Stergioulas; Anastasios Tefas (Appl. Soft Comput., 2023)

Deep label embedding learning for classification. - Paraskevi Nousi; Anastasios Tefas (Appl. Soft Comput., 2024)

AnIO: anchored input-output learning for time-series forecasting. - Ourania Stentoumi; Paraskevi Nousi; Maria Tzelepi; Anastasios Tefas (Neural Comput. Appl., 2024)

Deep reinforcement learning for financial trading using multi-modal features. - Loukia Avramelou; Paraskevi Nousi; Nikolaos Passalis; Anastasios Tefas (Expert Syst. Appl., 2024)

Vpit: real-time embedded single object 3D tracking using voxel pseudo images. - Illia Oleksiienko; Paraskevi Nousi; Nikolaos Passalis; Anastasios Tefas; Alexandros Iosifidis (Neural Comput. Appl., 2024)

New gravitational wave discoveries enabled by machine learning. - Alexandra E. Koloniari; Evdokia C. Koursoumpa; Paraskevi Nousi; Paraskevas Lampropoulos; Nikolaos Passalis; Anastasios Tefas; Nikolaos Stergioulas (Mach. Learn. Sci. Technol., 2025)