Deep Learning on Multi Sensor Data for Counter UAV Applications—A Systematic Review

Autor: Stamatios Samaras, Eleni Diamantidou, Dimitrios Ataloglou, Nikos Sakellariou, Anastasios Vafeiadis, Vasilis Magoulianitis, Antonios Lalas, Anastasios Dimou, Dimitrios Zarpalas, Konstantinos Votis, Petros Daras, Dimitrios Tzovaras

Publikováno v: Sensors, Vol 19, Iss 22, p 4837 (2019)

Usage of Unmanned Aerial Vehicles (UAVs) is growing rapidly in a wide range of consumer applications, as they prove to be both autonomous and flexible in a variety of environments and tasks. However, this versatility and ease of use also brings a rap

Externí odkaz: https://doaj.org/article/e62ff08fb7d94499bc0b0b92da1ecf19

A Novel Image and Audio-based Artificial Intelligence Service for Security Applications in Autonomous Vehicles (Extended version)

Autor: Dimitrios Tsiktsiris, Anastasios Vafeiadis, Antonios Lalas, Minas Dasygenis, Konstantinos Votis, Dimitrios Tzovaras

Publikováno v: Transportation Research Procedia-24th Euro Working Group on Transportation Meeting 2021

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=r3c4b2081b22::d14cf93a1d17a35f71f50e76e6a49150

Audio-Based Event Detection at Different SNR Settings Using Two-Dimensional Spectrogram Magnitude Representations

Autor: Ioannis Papadimitriou, Antonios Lalas, Dimitrios Tzovaras, Konstantinos Votis, Anastasios Vafeiadis

Publikováno v: Electronics
Volume 9
Issue 10
Electronics, Vol 9, Iss 1593, p 1593 (2020)

Audio-based event detection poses a number of different challenges that are not encountered in other fields, such as image detection. Challenges such as ambient noise, low Signal-to-Noise Ratio (SNR) and microphone distance are not yet fully understo

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::087bc75116265b1143c87382cc14037b

Feature learning for human activity recognition using convolutional neural networks: A case study for inertial measurement unit and audio data

Autor: Raouf Hamzaoui, Paul McCullagh, Liming Chen, Federico Cruciani, Konstantinos Votis, Anastasios Vafeiadis, Chris D. Nugent, Dimitrios Tzovaras, Ian Cleland, Dimitrios Giakoumis

The use of Convolutional Neural Networks (CNNs) as a feature learning method for Human Activity Recognition (HAR) is becoming more and more common. Unlike conventional machine learning methods, which require domain-specific expertise, CNNs can extrac

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5b922b9f1b5446e3f4ec08aeb1170939
https://dora.dmu.ac.uk/handle/2086/19101

Image-based Text Classification using 2D Convolutional Neural Networks

Autor: Dimitrios Tzovaras, Dimitrios Giakoumis, Liming Chen, Joahannes Kroph, Erinc Merdivan, Matthieu Geist, Anastasios Vafeiadis, Raouf Hamzaoui, Dimitrios Kalatzis, Konstantinos Votis, Sten Hanke

Publikováno v: 2019 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI)
2019 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI), Aug 2019, Leicester, United Kingdom. pp.144-149, ⟨10.1109/SmartWorld-UIC-ATC-SCALCOM-IOP-SCI.2019.00066⟩
SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI

International audience; We propose a new approach to text classificationin which we consider the input text as an image and apply2D Convolutional Neural Networks to learn the local andglobal semantics of the sentences from the variations of thevisual

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e929c750e1e3932de1f2467cd7b4d428
https://www.dora.dmu.ac.uk/handle/2086/18112