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» Modeling Herds and Their Evolvements from Trajectory Data
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CVPR
2003
IEEE
16 years 1 months ago
Recognising and Monitoring High-Level Behaviours in Complex Spatial Environments
The recognition of activities from sensory data is important in advanced surveillance systems to enable prediction of high-level goals and intentions of the target under surveilla...
Nam Thanh Nguyen, Hung Hai Bui, Svetha Venkatesh, ...
KDD
2009
ACM
224views Data Mining» more  KDD 2009»
15 years 4 months ago
Issues in evaluation of stream learning algorithms
Learning from data streams is a research area of increasing importance. Nowadays, several stream learning algorithms have been developed. Most of them learn decision models that c...
João Gama, Raquel Sebastião, Pedro P...
FAST
2009
14 years 9 months ago
Provenance as Data Mining: Combining File System Metadata with Content Analysis
Provenance describes how an object came to be in its present state. Thus, it describes the evolution of the object over time. Prior work on provenance has focussed on databases an...
Vinay Deolalikar, Hernan Laffitte
ICCSA
2009
Springer
15 years 6 months ago
Learning and Predicting Key Web Navigation Patterns Using Bayesian Models
Abstract. The accurate prediction of Web navigation patterns has immense commercial value as the Web evolves into a primary medium for marketing and sales for many businesses. Ofte...
Malik Tahir Hassan, Khurum Nazir Junejo, Asim Kari...
TMI
2010
155views more  TMI 2010»
14 years 6 months ago
Tubular Surface Segmentation for Extracting Anatomical Structures From Medical Imagery
Abstract--This work provides a model for tubular structures, and devises an algorithm to automatically extract tubular anatomical structures from medical imagery. Our model fits ma...
Vandana Mohan, Ganesh Sundaramoorthi, Allen Tannen...