14 May 2018 Cognitive computer-on-watch: Applying artificial intelligence/machine learning to augment human capability (Conference Presentation)
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Abstract
Recent advances in Machine Learning have been built on massive amounts of labelled data. However, data labeling is an expensive exercise. Oftentimes, for rare objects of interest, there is not enough data. We present novel techniques to reduce the amount of data that needs to be labelled, as well to prioritize the data labeling task. We show results of applying our techniques to computer vision. Another critical need is to be able to adapt these computer vision techniques for on-board processing. We present results for on-board distributed detection and tracking using a team of UAVs that collaborate for tracking objects of interest on the ground.
Conference Presentation
© (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Sanjeev Mohindra, Arjun Majumdar, and Benjamin Smith "Cognitive computer-on-watch: Applying artificial intelligence/machine learning to augment human capability (Conference Presentation)", Proc. SPIE 10635, Ground/Air Multisensor Interoperability, Integration, and Networking for Persistent ISR IX, 106350A (14 May 2018); doi: 10.1117/12.2306033; https://doi.org/10.1117/12.2306033
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