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pro vyhledávání: '"Jeffrey T. Carlo"'
Autor:
Niki Pissinou, Todd B. Howlett, Jeffrey T. Carlo, Alexander Aved, Vasanth Iyer, S. Sitharama Iyengar, Asif Mehmood
Publikováno v:
Real-Time Image Processing and Deep Learning 2019.
The purpose of this paper is on the study of data fusion applications in traditional, spatial and aerial video stream applications which addresses the processing of data from multiple sources using co-occurrence information and uses a common semantic
Publikováno v:
Target and Background Signatures IV.
Traditional event detection from video frames are based on a batch or offline based algorithms: it is assumed that a single event is present within each video, and videos are processed, typically via a pre-processing algorithm which requires enormous
Publikováno v:
Proceedings of the 2003 IEEE Radar Conference (Cat. No. 03CH37474).
Traditionally, statistical space-time adaptive processing (STAP) approaches have been implemented to detect targets using an airborne radar system. These approaches typically assume a wide sense stationary environment and utilize auxiliary training d
Publikováno v:
Applications of Space-Time Adaptive Processing ISBN: 9780852969243
In this chapter, the authors have presented four deterministic direct data domain least-squares techniques for nulling interferers and extracting the signal of interest. This approach generates the adaptive weights on a snapshot-by-snapshot basis tha
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5e67363b164ac9cd68f10f6847bc4dd0
https://doi.org/10.1049/pbra014e_ch12
https://doi.org/10.1049/pbra014e_ch12
Publikováno v:
SPIE Proceedings.
Research in advanced surveillance systems concepts is actively being pursued throughout DoD. One flexible and cost effective way of evaluating the mission effectiveness of these system concepts is through the use of mission level simulations. This ap