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KI
2007
Springer
15 years 11 months ago
Location-Based Activity Recognition
Learning patterns of human behavior from sensor data is extremely important for high-level activity inference. We show how to extract and label a person’s activities and signiïŹ...
Dieter Fox
IJRR
2007
186views more  IJRR 2007»
15 years 4 months ago
Extracting Places and Activities from GPS Traces Using Hierarchical Conditional Random Fields
Learning patterns of human behavior from sensor data is extremely important for high-level activity inference. We show how to extract a person’s activities and signiïŹcant plac...
Lin Liao, Dieter Fox, Henry A. Kautz
CHI
2008
ACM
16 years 5 months ago
Activity sensing in the wild: a field trial of ubifit garden
Recent advances in small inexpensive sensors, low-power processing, and activity modeling have enabled applications that use on-body sensing and machine learning to infer people&#...
Sunny Consolvo, David W. McDonald, Tammy Toscos, M...
182
Voted
TMI
2010
182views more  TMI 2010»
15 years 3 months ago
A Bayesian Mixture Approach to Modeling Spatial Activation Patterns in Multisite fMRI Data
Abstract—We propose a probabilistic model for analyzing spatial activation patterns in multiple functional magnetic resonance imaging (fMRI) activation images such as repeated ob...
Seyoung Kim, Padhraic Smyth, Hal S. Stern
155
Voted
SIGIR
2010
ACM
15 years 5 months ago
SED: supervised experimental design and its application to text classification
In recent years, active learning methods based on experimental design achieve state-of-the-art performance in text classification applications. Although these methods can exploit ...
Yi Zhen, Dit-Yan Yeung