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328 results on '"Nikolaidis, Nikos"'

1. CARLA2Real: a tool for reducing the sim2real gap in CARLA simulator

Author

Pasios, Stefanos and Nikolaidis, Nikos

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Simulators are indispensable for research in autonomous systems such as self-driving cars, autonomous robots and drones. Despite significant progress in various simulation aspects, such as graphical realism, an evident gap persists between the virtual and real-world environments. Since the ultimate goal is to deploy the autonomous systems in the real world, closing the sim2real gap is of utmost importance. In this paper, we employ a state-of-the-art approach to enhance the photorealism of simulated data, aligning them with the visual characteristics of real-world datasets. Based on this, we developed CARLA2Real, an easy-to-use, publicly available tool (plug-in) for the widely used and open-source CARLA simulator. This tool enhances the output of CARLA in near real-time, achieving a frame rate of 13 FPS, translating it to the visual style and realism of real-world datasets such as Cityscapes, KITTI, and Mapillary Vistas. By employing the proposed tool, we generated synthetic datasets from both the simulator and the enhancement model outputs, including their corresponding ground truth annotations for tasks related to autonomous driving. Then, we performed a number of experiments to evaluate the impact of the proposed approach on feature extraction and semantic segmentation methods when trained on the enhanced synthetic data. The results demonstrate that the sim2real gap is significant and can indeed be reduced by the introduced approach., Comment: 22 pages

Published
2024

3. Deep Learning for Energy Time-Series Analysis and Forecasting

Author

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

Subjects
Computer Science - Machine Learning
Abstract

Energy time-series analysis describes the process of analyzing past energy observations and possibly external factors so as to predict the future. Different tasks are involved in the general field of energy time-series analysis and forecasting, with electric load demand forecasting, personalized energy consumption forecasting, as well as renewable energy generation forecasting being among the most common ones. Following the exceptional performance of Deep Learning (DL) in a broad area of vision tasks, DL models have successfully been utilized in time-series forecasting tasks. This paper aims to provide insight into various DL methods geared towards improving the performance in energy time-series forecasting tasks, with special emphasis in Greek Energy Market, and equip the reader with the necessary knowledge to apply these methods in practice., Comment: 13 papges, 4 figures

Published
2023

4. Potential UAV Landing Sites Detection through Digital Elevation Models Analysis

Author

Kakaletsis, Efstratios and Nikolaidis, Nikos

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Graphics, 68W40
Abstract

In this paper, a simple technique for Unmanned Aerial Vehicles (UAVs) potential landing site detection using terrain information through identification of flat areas, is presented. The algorithm utilizes digital elevation models (DEM) that represent the height distribution of an area. Flat areas which constitute appropriate landing zones for UAVs in normal or emergency situations result by thresholding the image gradient magnitude of the digital surface model (DSM). The proposed technique also uses connected components evaluation on the thresholded gradient image in order to discover connected regions of sufficient size for landing. Moreover, man-made structures and vegetation areas are detected and excluded from the potential landing sites. Quantitative performance evaluation of the proposed landing site detection algorithm in a number of areas on real world and synthetic datasets, accompanied by a comparison with a state-of-the-art algorithm, proves its efficiency and superiority., Comment: Proceedings of the 2019 27th European Signal Processing Conference (EUSIPCO) satellite workshop "Signal Processing Computer vision and Deep Learning for Autonomous Systems"

Published
2021

6. Wind Energy Prediction Guided by Multiple-Location Weather Forecasts

Author

Symeonidis, Charalampos, Nikolaidis, Nikos, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Barbosa, Simone Diniz Junqueira, Editorial Board Member, Chen, Phoebe, Editorial Board Member, Cuzzocrea, Alfredo, Editorial Board Member, Du, Xiaoyong, Editorial Board Member, Kara, Orhun, Editorial Board Member, Liu, Ting, Editorial Board Member, Sivalingam, Krishna M., Editorial Board Member, Slezak, Dominik, Editorial Board Member, Washio, Takashi, Editorial Board Member, Yang, Xiaokang, Editorial Board Member, Yuan, Junsong, Editorial Board Member, Iliadis, Lazaros, editor, Maglogiannis, Ilias, editor, Alonso, Serafin, editor, Jayne, Chrisina, editor, and Pimenidis, Elias, editor

Published
2023
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7. A multiple-UAV architecture for autonomous media production

Author

Mademlis, Ioannis, Torres-González, Arturo, Capitán, Jesús, Montagnuolo, Maurizio, Messina, Alberto, Negro, Fulvio, Le Barz, Cedric, Gonçalves, Tiago, Cunha, Rita, Guerreiro, Bruno, Zhang, Fan, Boyle, Stephen, Guerout, Gregoire, Tefas, Anastasios, Nikolaidis, Nikos, Bull, David, and Pitas, Ioannis

Published
2023
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12. List of contributors

Author

Ahishali, Mete, primary, Ahmad, Saad, additional, Angleraud, Alexandre, additional, Bardakci, Deniz, additional, Chowdhury, Muhammad E.H., additional, Chumachenko, Kateryna, additional, Degerli, Aysen, additional, Esterle, Lukas, additional, Gabbouj, Moncef, additional, Hedegaard, Lukas, additional, Heidari, Negar, additional, Hurtado, Juana Valeria, additional, Ince, Turker, additional, Iosifidis, Alexandros, additional, Kayacan, Erdal, additional, Kiranyaz, Serkan, additional, Kirtas, Manos, additional, Le Fevre, Jonas, additional, Mehman Sefat, Amir, additional, Nikolaidis, Nikos, additional, Nousi, Paraskevi, additional, Oleksiienko, Illia, additional, Passalis, Nikolaos, additional, Pham, Huy Xuan, additional, Pieters, Roel, additional, Rahtu, Esa, additional, Raitoharju, Jenni, additional, Symeonidis, Charalampos, additional, Tefas, Anastasios, additional, Tosidis, Pavlos, additional, Tran, Dat Thanh, additional, Tsampazis, Konstantinos, additional, Tsantekidis, Avraam, additional, Tzelepi, Maria, additional, Ugurlu, Halil Ibrahim, additional, Valada, Abhinav, additional, Yamac, Mehmet, additional, and Zaras, Adamantios, additional

Published
2022
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14. Efficient Deterministic Renewable Energy Forecasting Guided by Multiple-Location Weather Data

Author

Symeonidis, Charalampos, Nikolaidis, Nikos, Symeonidis, Charalampos, and Nikolaidis, Nikos

Abstract

Electricity generated from renewable energy sources has been established as an efficient remedy for both energy shortages and the environmental pollution stemming from conventional energy production methods. Solar and wind power are two of the most dominant renewable energy sources. The accurate forecasting of the energy generation of those sources facilitates their integration into electric grids, by minimizing the negative impact of uncertainty regarding their management and operation. This paper proposes a novel methodology for deterministic wind and solar energy generation forecasting for multiple generation sites, utilizing multi-location weather forecasts. The method employs a U-shaped Temporal Convolutional Auto-Encoder (UTCAE) architecture for temporal processing of weather-related and energy-related time-series across each site. The Multi-sized Kernels convolutional Spatio-Temporal Attention (MKST-Attention), inspired by the multi-head scaled-dot product attention mechanism, is also proposed aiming to efficiently transfer temporal patterns from weather data to energy data, without a priori knowledge of the locations of the power stations and the locations of provided weather data. The conducted experimental evaluation on a day-ahead solar and wind energy forecasting scenario on five datasets demonstrated that the proposed method achieves top results, outperforming all competitive time-series forecasting state-of-the-art methods.

Published
2024

15. Semantic Map Annotation Through UAV Video Analysis Using Deep Learning Models in ROS

Author

Kakaletsis, Efstratios, Tzelepi, Maria, Kaplanoglou, Pantelis I., Symeonidis, Charalampos, Nikolaidis, Nikos, Tefas, Anastasios, Pitas, Ioannis, Hutchison, David, Series Editor, Kanade, Takeo, Series Editor, Kittler, Josef, Series Editor, Kleinberg, Jon M., Series Editor, Mattern, Friedemann, Series Editor, Mitchell, John C., Series Editor, Naor, Moni, Series Editor, Pandu Rangan, C., Series Editor, Steffen, Bernhard, Series Editor, Terzopoulos, Demetri, Series Editor, Tygar, Doug, Series Editor, Weikum, Gerhard, Series Editor, Kompatsiaris, Ioannis, editor, Huet, Benoit, editor, Mezaris, Vasileios, editor, Gurrin, Cathal, editor, Cheng, Wen-Huang, editor, and Vrochidis, Stefanos, editor

Published
2019
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22. Multimodal Speaker Diarization Utilizing Face Clustering Information

Author

Kapsouras, Ioannis, Tefas, Anastasios, Nikolaidis, Nikos, Pitas, Ioannis, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, and Zhang, Yu-Jin, editor

Published
2015
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28. Using Haptic-Based Trajectory Following in 3D Space to Distinguish between Men and Women

Author

Zarogianni, Eleni, Marras, Ioannis, Nikolaidis, Nikos, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Kappers, Astrid M. L., editor, van Erp, Jan B. F., editor, Bergmann Tiest, Wouter M., editor, and van der Helm, Frans C. T., editor

Published
2010
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32. Computationally Efficient Image Mosaicing Using Spanning Tree Representations

Author

Nikolaidis, Nikos, Pitas, Ioannis, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Dough, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Bozanis, Panayiotis, editor, and Houstis, Elias N., editor

Published
2005
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42. A multiple-UAV architecture for autonomous media production

Author

Mademlis, Ioannis, primary, Torres-González, Arturo, additional, Capitán, Jesús, additional, Montagnuolo, Maurizio, additional, Messina, Alberto, additional, Negro, Fulvio, additional, Le Barz, Cedric, additional, Gonçalves, Tiago, additional, Cunha, Rita, additional, Guerreiro, Bruno, additional, Zhang, Fan, additional, Boyle, Stephen, additional, Guerout, Gregoire, additional, Tefas, Anastasios, additional, Nikolaidis, Nikos, additional, Bull, David, additional, and Pitas, Ioannis, additional

Published
2022
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50. Computer Vision for Autonomous UAV Flight Safety: An Overview and a Vision-based Safe Landing Pipeline Example.

Author

KAKALETSIS, EFSTRATIOS, SYMEONIDIS, CHARALAMPOS, TZELEPI, MARIA, MADEMLIS, IOANNIS, TEFAS, ANASTASIOS, NIKOLAIDIS, NIKOS, and PITAS, IOANNIS

Subjects
COMPUTER vision, LANDING (Aeronautics), DRONE aircraft, WILDLIFE monitoring, RESCUE work
Abstract

Recent years have seen an unprecedented spread of Unmanned Aerial Vehicles (UAVs, or "drones"), which are highly useful for both civilian and military applications. Flight safety is a crucial issue in UAV navigation, having to ensure accurate compliance with recently legislated rules and regulations. The emerging use of autonomous drones and UAV swarms raises additional issues, making it necessary to transfuse safety- and regulations-awareness to relevant algorithms and architectures. Computer vision plays a pivotal role in such autonomous functionalities. Although themain aspects of autonomous UAV technologies (e.g., path planning, navigation control, landing control, mapping and localization, target detection/tracking) are already mature and well-covered, ensuring safe lying in the vicinity of crowds, avoidance of passing over persons, or guaranteed emergency landing capabilities in case of malfunctions, are generally treated as an afterthought when designing autonomous UAV platforms for unstructured environments. This fact is relected in the fragmentary coverage of the above issues in current literature. This overview attempts to remedy this situation, from the point of view of computer vision. It examines the ield from multiple aspects, including regulations across the world and relevant current technologies. Finally, since very few attempts have been made so far towards a complete UAV safety light and landing pipeline, an example computer vision-based UAV light safety pipeline is introduced, taking into account all issues present in current autonomous drones. The content is relevant to any kind of autonomous drone light (e.g., for movie/TV production, news-gathering, search and rescue, surveillance, inspection, mapping, wildlife monitoring, crowd monitoring/management), making this a topic of broad interest. [ABSTRACT FROM AUTHOR]

Published
2022
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