Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Chris Capraro"'
Autor:
Nathan Inkawhich, Matthew J. Inkawhich, Eric K. Davis, Uttam K. Majumder, Erin Tripp, Chris Capraro, Yiran Chen
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 14, Pp 2942-2955 (2021)
Obtaining measured synthetic aperture radar (SAR) data for training automatic target recognition (ATR) models can be too expensive (in terms of time and money) and complex of a process in many situations. In response, researchers have developed metho
Externí odkaz:
https://doaj.org/article/356c7363d8704a60a64d03178bb4743b
Publikováno v:
Algorithms for Synthetic Aperture Radar Imagery XXVII.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::04b599362bd6df13ba2447ee9f9b3616
https://doi.org/10.1117/12.2560677
https://doi.org/10.1117/12.2560677
Publikováno v:
Algorithms for Synthetic Aperture Radar Imagery XXVII.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a037883b0ce992f54071b55a5bffd5be
https://doi.org/10.1117/12.2560672
https://doi.org/10.1117/12.2560672
Publikováno v:
2020 IEEE International Radar Conference (RADAR).
We present advanced Deep Learning (DL) techniques for robust Synthetic Aperture Radar (SAR) automatic target recognition (ATR) in the presence of noise and signal phase errors. Our research focuses on ensuring robust performance of SAR ATR algorithms
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2be8ca518dd8f42f564f470390914bf4
https://doi.org/10.1109/radar42522.2020.9114784
https://doi.org/10.1109/radar42522.2020.9114784
Publikováno v:
Algorithms for Synthetic Aperture Radar Imagery XXVI.
This research details a new approach to optimize neural network architectures for Synthetic Aperture Radar (SAR) object classification on neuromorphic (e.g., IBM’s TrueNorth) and embedded platforms. We developed an algorithm to reduce the run-time
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::41d9bfa662e9a86242f55b1ec4d2a416
https://doi.org/10.1117/12.2520625
https://doi.org/10.1117/12.2520625
Publikováno v:
Cyber Sensing 2019.
Among various parameters, large scene object detection and classification accuracy depends on image quality. In general, deep neural networks (DNN) are trained to achieve a desired recognition accuracy on a set of targets. However, DNNs become tuned
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ed22334a21682d122268a553b26eb19d
https://doi.org/10.1117/12.2520618
https://doi.org/10.1117/12.2520618
Publikováno v:
HPEC
For the first time ever, advanced machine learning (ML) compute architectures, techniques, and methods were demonstrated in flight (in June-August 2017 and May 2018) on the recently invented high-performance computing (HPC) architecture called Agile
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::28faaca65bbff37a28af56f6856c05ea
https://doi.org/10.1109/hpec.2018.8547797
https://doi.org/10.1109/hpec.2018.8547797
Publikováno v:
2018 IEEE Aerospace Conference.
Data fusion algorithms exploit multiple, independent sensors to obtain improved estimates of the state of a system. Recent progress in sheaf theory has yielded a general approach for translating data fusion problems into optimization problems. This a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f648b5961a1eca56d259db7163bab3e3
https://doi.org/10.1109/aero.2018.8396546
https://doi.org/10.1109/aero.2018.8396546