This paper explores the use of alternating sequential patterns of local features and saccading actions to learn robust and compact object representations. The temporal encoding rep...
Abstract. We present a detection-based three-level hierarchical association approach to robustly track multiple objects in crowded environments from a single camera. At the low lev...
This paper discusses our approach to building models and analyzing student behaviors in different versions of our learning by teaching environment where students learn by teaching ...
This paper presents an approach for mining fuzzy Association Rules (ARs) relating the properties of composite items, i.e. items that each feature a number of values derived from a ...
Based on simple methods such as observing word and part of speech tag co-occurrence and clustering, we generate syntactic parses of sentences in an entirely unsupervised and self-...