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GTC ON-DEMAND

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Abstract:
We'll discuss practical applications of state-of-the-art convolutional neural networks (CNNs) to the challenges of surveillance systems. We'll discuss modifications to a current state-of-the-art neural network to improve detection of small targets while maintaining detection performance on larger targets. We'll then discuss a novel sensor-fusion method to improve small target localization and provide track classification to a fused common operating picture. We'll present results from the MS-COCO dataset and from data collected on our own testbed, which recorded small quadcopters in flight using a commercial surveillance camera. Finally, we'll discuss how our novel CNN detection and sensor fusion algorithms can be used to enable surveillance security applications. Sponsor: DHS S&T.
We'll discuss practical applications of state-of-the-art convolutional neural networks (CNNs) to the challenges of surveillance systems. We'll discuss modifications to a current state-of-the-art neural network to improve detection of small targets while maintaining detection performance on larger targets. We'll then discuss a novel sensor-fusion method to improve small target localization and provide track classification to a fused common operating picture. We'll present results from the MS-COCO dataset and from data collected on our own testbed, which recorded small quadcopters in flight using a commercial surveillance camera. Finally, we'll discuss how our novel CNN detection and sensor fusion algorithms can be used to enable surveillance security applications. Sponsor: DHS S&T.  Back
 
Topics:
Cyber Security, Intelligent Video Analytics
Type:
Talk
Event:
GTC Washington D.C.
Year:
2017
Session ID:
DC7180
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