Zobrazeno 1 - 10
of 17
pro vyhledávání: '"George Matich"'
Publikováno v:
Frontiers in Neurorobotics, Vol 14 (2020)
Traditionally the Perception Action cycle is the first stage of building an autonomous robotic system and a practical way to implement a low latency reactive system within a low Size, Weight and Power (SWaP) package. However, within complex scenarios
Externí odkaz:
https://doaj.org/article/a60a374b77874a3b9da26b6f1c0ac762
Publikováno v:
Radar Countermeasures for Unmanned Aerial Vehicles ISBN: 9781839531903
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::92827689a7127bec5cc457c7534ce316
https://doi.org/10.1049/sbra543e_ch2
https://doi.org/10.1049/sbra543e_ch2
Publikováno v:
Frontiers in Neurorobotics, Vol 14 (2020)
Frontiers in Neurorobotics
Frontiers in Neurorobotics
Traditionally the Perception Action cycle is the first stage of building an autonomous robotic system and a practical way to implement a low latency reactive system within a low Size, Weight and Power (SWaP) package. However, within complex scenarios
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::05e7e7c87ba8fb0989f3dae82e9e615e
https://strathprints.strath.ac.uk/73808/7/Kirkland_etal_FN_2020_adding_understanding_to_the_perception_action_cycle_with_spiking_segmentation.pdf
https://strathprints.strath.ac.uk/73808/7/Kirkland_etal_FN_2020_adding_understanding_to_the_perception_action_cycle_with_spiking_segmentation.pdf
Publikováno v:
IJCNN
Taking inspiration from the structure and behaviour of the human visual system and using the Transposed Convolution and Saliency Mapping methods of Convolutional Neural Networks (CNN), a spiking event-based image segmentation algorithm, SpikeSEG is p
UAV Detection: A STDP Trained Deep Convolutional Spiking Neural Network Retina-Neuromorphic Approach
Publikováno v:
Artificial Neural Networks and Machine Learning – ICANN 2019: Theoretical Neural Computation ISBN: 9783030304867
ICANN (1)
28th International Conference on Artificial Neural Networks 2019
ICANN (1)
28th International Conference on Artificial Neural Networks 2019
The Dynamic Vision Sensor (DVS) has many attributes, such as sub-millisecond response time along with a good low light dy- namic range, that allows it to be well suited to the task for UAV De- tection. This paper proposes a system that exploits the f
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::30a0c608e0dcda8976485dead4d6bc8e
https://doi.org/10.1007/978-3-030-30487-4_56
https://doi.org/10.1007/978-3-030-30487-4_56
Publikováno v:
Artificial Neural Networks and Machine Learning – ICANN 2018 ISBN: 9783030014179
ICANN (1)
27th International Conference on Artificial Neural Networks
ICANN (1)
27th International Conference on Artificial Neural Networks
Convolutional Neural Networks (CNNs) have exhibited certain human-like performance on computer vision related tasks. Over the past few years since they have outperformed conventional algorithms in a range of image processing problems. However, to uti
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::95a9a7a4eb7b87669f1b54d732c338af
https://doi.org/10.1007/978-3-030-01418-6_78
https://doi.org/10.1007/978-3-030-01418-6_78
Publikováno v:
IET Wireless Sensor Systems. 1:229-240
A system termed VIGILANT+ is outlined, which utilises situation awareness for the purposes of enabling distributed, autonomic, sensor management, so that savings on consumption of network resources can be achieved. VIGILANT+ is a novel proposition al
Publikováno v:
IEEE Communications Magazine
Distributed unattended ground sensor networks used in battlefield surveillance and monitoring missions, have proven to be valuable in providing a tactical information advantage required for command and control, intelligence, surveillance, and reconna
Publikováno v:
2014 IEEE Military Communications Conference.
This paper presents a remote, undetectable, high accuracy mechanism to infer Skype voice traffic on WiFi networks with a success rate of ?97% and only a ?3% false positive rate. In spite of any encryption scheme employed, we infer user activity by ex
Publikováno v:
SOSE
This paper documents a hardware and software implementation to monitor, capture and store encrypted WiFi communication data. The implementation detailed can perform this entirely passively using only cheap commodity hardware and freely available soft