Paraskevi Nousi

According to our database, Paraskevi Nousi authored at least 32 papers between 2017 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Deep reinforcement learning for financial trading using multi-modal features.

Loukia Avramelou, Paraskevi Nousi, Nikolaos Passalis, Anastasios Tefas

Expert Syst. Appl., March, 2024

AnIO: anchored input-output learning for time-series forecasting.

Ourania Stentoumi, Paraskevi Nousi, Maria Tzelepi, Anastasios Tefas

Neural Comput. Appl., February, 2024

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., November, 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, Anastasios Tefas

CoRR, 2023

Deep Learning for Energy Time-Series Analysis and Forecasting.

Maria Tzelepi, Charalampos Symeonidis, Paraskevi Nousi, Efstratios Kakaletsis, Theodoros Manousis, Pavlos Tosidis, Nikos Nikolaidis, Anastasios Tefas

CoRR, 2023

Variational Voxel Pseudo Image Tracking.

Illia Oleksiienko, Paraskevi Nousi, Nikolaos Passalis, Anastasios Tefas, Alexandros Iosifidis

Proceedings of the IEEE Symposium Series on Computational Intelligence, 2023

Anchored Input-Output Learning for Electrical Load Demand Forecasting.

Paraskevi Nousi, Maria Tzelepi, Anastasios Tefas

Proceedings of the IEEE International Symposium on Circuits and Systems, 2023

A Sharpe Ratio Based Reward Scheme in Deep Reinforcement Learning for Financial Trading.

Georgios Rodinos, Paraskevi Nousi, Nikolaos Passalis, Anastasios Tefas

Proceedings of the Artificial Intelligence Applications and Innovations, 2023

Improving Electric Load Demand Forecasting with Anchor-Based Forecasting Method.

Maria Tzelepi, Paraskevi Nousi, Anastasios Tefas

Proceedings of the IEEE International Conference on Acoustics, 2023

Cryptosentiment: A Dataset and Baseline for Sentiment-Aware Deep Reinforcement Learning for Financial Trading.

Loukia Avramelou, Paraskevi Nousi, Nikolaos Passalis, Stavros Doropoulos, Anastasios Tefas

Proceedings of the IEEE International Conference on Acoustics, 2023

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

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

MLGWSC-1: The first Machine Learning Gravitational-Wave Search Mock Data Challenge.

Marlin B. Schäfer, Ondrej Zelenka, Alexander H. Nitz, He Wang, Shichao Wu, Zong-Kuan Guo, Zhoujian Cao, Zhixiang Ren, Paraskevi Nousi, Nikolaos Stergioulas, Panagiotis Iosif, Alexandra E. Koloniari, Anastasios Tefas, Nikolaos Passalis, Francesco Salemi, Gabriele Vedovato, Sergey Klimenko, Tanmaya Mishra, Bernd Brügmann, Elena Cuoco, E. A. Huerta, Chris Messenger, Frank Ohme

CoRR, 2022

VPIT: Real-time Embedded Single Object 3D Tracking Using Voxel Pseudo Images.

Illia Oleksiienko, Paraskevi Nousi, Nikolaos Passalis, Anastasios Tefas, Alexandros Iosifidis

CoRR, 2022

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, E. Kayacan, Jens Kober, O. Michel, Nikos Nikolaidis, Paraskevi Nousi, Roel Pieters, Maria Tzelepi, Abhinav Valada, Anastasios Tefas

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2022

2021

Supervised and unsupervised deep learning methodologies

Paraskevi Nousi

PhD thesis, 2021

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

Proceedings of the 22nd Engineering Applications of Neural Networks Conference, 2021

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

Deep autoencoders for attribute preserving face de-identification.

Paraskevi Nousi, Sotirios Papadopoulos, Anastasios Tefas, Ioannis Pitas

Signal Process. Image Commun., 2020

Dense convolutional feature histograms for robust visual object tracking.

Paraskevi Nousi, Anastasios Tefas, Ioannis Pitas

Image Vis. Comput., 2020

Self-supervised autoencoders for clustering and classification.

Paraskevi Nousi, Anastasios Tefas

Evol. Syst., 2020

Visual Object Detection For Autonomous UAV Cinematography.

Fotini Patrona, Paraskevi Nousi, Ioannis Mademlis, Anastasios Tefas, Ioannis Pitas

Proceedings of the 2020 Northern Lights Deep Learning Workshop, 2020

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

Embedded UAV Real-Time Visual Object Detection and Tracking.

Paraskevi Nousi, Ioannis Mademlis, Iason Karakostas, Anastasios Tefas, Ioannis Pitas

Proceedings of the 2019 IEEE International Conference on Real-time Computing and Robotics, 2019

Joint Lightweight Object Tracking and Detection for Unmanned Vehicles.

Paraskevi Nousi, Danai Triantafyllidou, Anastasios Tefas, Ioannis Pitas

Proceedings of the 2019 IEEE International Conference on Image Processing, 2019

Deep Convolutional Feature Histograms for Visual Object Tracking.

Paraskevi Nousi, Anastasios Tefas, Ioannis Pitas

Proceedings of the IEEE International Conference on Acoustics, 2019

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

Fast Deep Convolutional Face Detection in the Wild Exploiting Hard Sample Mining.

Danai Triantafyllidou, Paraskevi Nousi, Anastasios Tefas

Big Data Res., 2018

Convolutional Neural Networks for Visual Information Analysis with Limited Computing Resources.

Paraskevi Nousi, Emmanouil Patsiouras, Anastasios Tefas, Ioannis Pitas

Proceedings of the 2018 IEEE International Conference on Image Processing, 2018

2017

Deep learning algorithms for discriminant autoencoding.

Paraskevi Nousi, Anastasios Tefas

Neurocomputing, 2017

Lightweight two-stream convolutional face detection.

Danai Triantafyllidou, Paraskevi Nousi, Anastasios Tefas

Proceedings of the 25th European Signal Processing Conference, 2017

Discriminatively Trained Autoencoders for Fast and Accurate Face Recognition.

Paraskevi Nousi, Anastasios Tefas

Proceedings of the Engineering Applications of Neural Networks, 2017