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» Feature Construction for Relational Sequence Learning
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PAMI
2006
206views more  PAMI 2006»
14 years 11 months ago
MILES: Multiple-Instance Learning via Embedded Instance Selection
Multiple-instance problems arise from the situations where training class labels are attached to sets of samples (named bags), instead of individual samples within each bag (called...
Yixin Chen, Jinbo Bi, James Ze Wang
ICPR
2004
IEEE
16 years 24 days ago
Recognizing Human Actions: A Local SVM Approach
Local space-time features capture local events in video and can be adapted to the size, the frequency and the velocity of moving patterns. In this paper we demonstrate how such fe...
Christian Schüldt, Ivan Laptev, Barbara Caput...
ICML
2000
IEEE
16 years 15 days ago
Maximum Entropy Markov Models for Information Extraction and Segmentation
Hidden Markov models (HMMs) are a powerful probabilistic tool for modeling sequential data, and have been applied with success to many text-related tasks, such as part-of-speech t...
Andrew McCallum, Dayne Freitag, Fernando C. N. Per...
PR
2008
218views more  PR 2008»
14 years 11 months ago
Automatic feature localisation with constrained local models
We present an efficient and robust method of locating a set of feature points in an object of interest. From a training set we construct a joint model of the appearance of each fe...
David Cristinacce, Timothy F. Cootes
PAMI
2000
113views more  PAMI 2000»
14 years 11 months ago
Hierarchical Discriminant Regression
This paper presents a new technique which incrementally builds a hierarchical discriminant regression (IHDR) tree for generation of motion based robot reactions. The robot learned...
Wey-Shiuan Hwang, Juyang Weng