Abstract. An efficient low-level word image representation plays a crucial role in general cursive word recognition. This paper proposes a novel representation scheme, where a word...
Jian-xiong Dong, Adam Krzyzak, Ching Y. Suen, Domi...
Subspace clustering is an extension of traditional clustering that seeks to find clusters in different subspaces within a dataset. This is a particularly important challenge with...
Abstract. A statistical technique is developed for estimating the support of itemsets on data streams, regardless of the size of the data stored. This technique, which is computati...
Pierre-Alain Laur, Jean-Emile Symphor, Richard Noc...
We estimate the speed of texture change by measuring the spread of texture vectors in their feature space. This method allows us to robustly detect even very slow moving objects. B...
Longin Jan Latecki, Roland Miezianko, Dragoljub Po...
In supervised machine learning, the partitioning of the values (also called grouping) of a categorical attribute aims at constructing a new synthetic attribute which keeps the info...
Textual Entailment recognition is a very difficult task as it is one of the fundamental problems in any semantic theory of natural language. As in many other NLP tasks, Machine Lea...
Maria Teresa Pazienza, Marco Pennacchiotti, Fabio ...
In this paper we present lessons learned in the Evaluating Predictive Uncertainty Challenge. We describe the methods we used in regression challenges, including our winning method ...
The Recognizing Textual Entailment System shown here is based on the use of a broad-coverage parser to extract dependency relationships; in addition, WordNet relations are used to ...
This paper describes the Bar-Ilan system participating in the Recognising Textual Entailment Challenge. The paper proposes first a general probabilistic setting that formalizes th...
The PASCAL Visual Object Classes Challenge ran from February to March 2005. The goal of the challenge was to recognize objects from a number of visual object classes in realistic s...
Mark Everingham, Andrew Zisserman, Christopher K. ...