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ICML
2001
IEEE
16 years 5 months ago
Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data
We present conditional random fields, a framework for building probabilistic models to segment and label sequence data. Conditional random fields offer several advantages over hid...
John D. Lafferty, Andrew McCallum, Fernando C. N. ...
ISBI
2002
IEEE
16 years 5 months ago
Capturing contextual dependencies in medical imagery using hierarchical multi-scale models
In this paper we summarize our results for two classes of hierarchical multi-scale models that exploit contextual information for detection of structure in mammographic imagery. T...
Paul Sajda, Clay Spence, Lucas C. Parra
ICMCS
2007
IEEE
132views Multimedia» more  ICMCS 2007»
15 years 10 months ago
Two-Layer Generative Models for Sport Video Mining
We present a two-layer generative model for sport video mining that is composed of a two-layer observation model. The first layer is the Gaussian mixture model (GMM) using framew...
Yi Ding, Guoliang Fan, W. Bryan
CAISE
2008
Springer
15 years 6 months ago
Assigning Ontology-Based Semantics to Process Models: The Case of Petri Nets
Syntactically correct process models are not necessarily meaningful or represent processes that are feasible to execute. Specifically, when executed, the modeled processes might no...
Pnina Soffer, Maya Kaner, Yair Wand
ER
2007
Springer
125views Database» more  ER 2007»
15 years 10 months ago
On the Correlation between Process Model Metrics and Errors
Business process models play an important role for the management, design, and improvement of process organizations and process-aware information systems. Despite the extensive ap...
Jan Mendling, Gustaf Neumann, Wil M. P. van der Aa...