Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Gary Chern"'
Publikováno v:
AIPR
GATR™ (Globally-scalable Automated Target Recognition) is a software system for object detection and classification on a worldwide basis developed by Lockheed Martin. One of the targets it detects are oil/gas fracking wells. In this work we explore
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d62700dfdda378d7f982af9aa2376416
https://doi.org/10.1109/aipr50011.2020.9425148
https://doi.org/10.1109/aipr50011.2020.9425148
Autor:
Stephen O'Neill, Mark D. Pritt, Austen Groener, Tyler Kuhns, Andy Lam, Michael Harner, Gary Chern
Publikováno v:
AIPR
GATR (Globally-scalable Automated Target Recognition) is a Lockheed Martin software system for real-time object detection and classification in satellite imagery on a worldwide basis. GATR uses GPU-accelerated deep learning software to quickly search
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fb41a3894cb532bea22bac4d3045db0d
http://arxiv.org/abs/2009.04836
http://arxiv.org/abs/2009.04836
Publikováno v:
AIPR
In this work, we compare the detection accuracy and speed of several state-of-the-art models for the task of detecting oil and gas fracking wells and small cars in commercial electro-optical satellite imagery. Several models are studied from the sing
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9f014b93b2699fd6983b9300a0ea9348
Publikováno v:
AIPR
The low/no-shot problem refers to a lack of available data for training deep learning algorithms. In remote sensing, complete image data sets are rare and do not always include the targets of interest. We propose a method to rapidly generate highfide
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bda0dd138f235d3d7c59d05b075aa6eb
https://doi.org/10.1109/aipr47015.2019.9174596
https://doi.org/10.1109/aipr47015.2019.9174596
Autor:
Gary Chern, Mark D. Pritt
Publikováno v:
AIPR
Satellite imagery is important for many applications including disaster response, law enforcement, and environmental monitoring. These applications require the manual identification of objects and facilities in the imagery. Because the geographic exp
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::67f2ba1b5a55331aba83fbf5d46a3b89
https://doi.org/10.1109/aipr.2017.8457969
https://doi.org/10.1109/aipr.2017.8457969