- Read more about EPILEPTIFORM SPIKE DETECTION VIA CONVOLUTIONAL NEURAL NETWORKS
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- Read more about Characterization and Classification of Sonar Targets Using Ellipsoid Features
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We present a geometry-inspired characterization of
target response for active sonar that exploits similarity between
intra-class features to distinguish between different targets
against environmental objects such as a rock. Key innovation is to
represent feature manifolds as a set of ellipsoids, each of which
geometrically encompasses a unique physical characteristic of
the target’s response. We have demonstrated over experimental
field data that for a given target class, these feature ellipsoids
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- Read more about Kernel-based low-rank feature extraction on a budget for Big data streams
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- Read more about 3D Object Modeling and Recognition via Online Hierarchical Pitman-Yor Process Mixture Learning
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Presentation slides covering:
- robust foreground detection / background subtraction via patch-based analysis
- person re-identification based on representations on Riemannian manifolds
- robust object tracking via Grassmann manifolds
- adapting the lessons from big data to computer vision
- future paradigm shifts: computer vision based on networks of neurosynaptic cores
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