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Applying Deep Learning to Improve Maritime Situational Awareness
| Content Provider | Semantic Scholar |
|---|---|
| Author | Tang, Kathy Stottler |
| Copyright Year | 2016 |
| Abstract | We describe a system called ExPATSS (Extensible Platform for Automated Tactical Sensor Screening) that we are developing for the Navy to automatically detect and classify ships from onboard an aircraft carrier. ExPATSS simultaneously processes several video streams for ship detection and classification, in order to reduce the attention and concentration currently required of human sensor operators, who presently have to manually monitor all the video streams at once. ExPATSS leverages recent developments in deep learning, specifically Convolutional Neural Networks (CNN), to accurately detect and classify ships. ExPATSS has been developed and tested using real-world data and this paper discusses the effectiveness of using CNN within the system. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | https://www.stottlerhenke.com/wp-content/uploads/2016/09/ExPATSS-Kdd-Paper-v7.pdf |
| Alternate Webpage(s) | https://www.stottlerhenke.com/wp-content/uploads/2016/08/KDD-Presentation_Kathy_v2.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
