This paper addresses the discovery of activities and learns the underlying processes that govern their occurrences over time in complex surveillance scenes. To this end, we propos...
Recently, we proposed marginal space learning (MSL) as
a generic approach for automatic detection of 3D anatom-
ical structures in many medical imaging modalities. To
accurately...
We present an efficient method for learning part-based object class models from unsegmented images represented as sets of salient features. A model includes parts' appearance...
We present a detailed study of network evolution by analyzing four large online social networks with full temporal information about node and edge arrivals. For the first time at ...
Jure Leskovec, Lars Backstrom, Ravi Kumar, Andrew ...
Large highly distributed data sets are poorly supported by current query technologies. Applications such as endsystembased network management are characterized by data stored on l...
Dushyanth Narayanan, Austin Donnelly, Richard Mort...