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» Mobile learning: A framework and evaluation
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ICRA
2005
IEEE
138views Robotics» more  ICRA 2005»
14 years 2 months ago
Urban Object Recognition from Informative Local Features
Abstract— Autonomous mobile agents require object recognition for high level interpretation and localization in complex scenes. In urban environments, recognition of buildings mi...
Gerald Fritz, Christin Seifert, Lucas Paletta
ECCV
2008
Springer
14 years 11 months ago
Weakly Supervised Object Localization with Stable Segmentations
Multiple Instance Learning (MIL) provides a framework for training a discriminative classifier from data with ambiguous labels. This framework is well suited for the task of learni...
Carolina Galleguillos, Boris Babenko, Andrew Rabin...
KDD
2010
ACM
222views Data Mining» more  KDD 2010»
13 years 11 months ago
Large linear classification when data cannot fit in memory
Recent advances in linear classification have shown that for applications such as document classification, the training can be extremely efficient. However, most of the existing t...
Hsiang-Fu Yu, Cho-Jui Hsieh, Kai-Wei Chang, Chih-J...
AGILEDC
2005
IEEE
14 years 2 months ago
Student Experiences with Executable Acceptance Testing
This report describes experiences of introducing executable acceptance testing in senior software engineering courses. Students in an agile environment completed a five-iteration ...
Kris Read, Grigori Melnik, Frank Maurer
NIPS
2004
13 years 10 months ago
Object Classification from a Single Example Utilizing Class Relevance Metrics
We describe a framework for learning an object classifier from a single example. This goal is achieved by emphasizing the relevant dimensions for classification using available ex...
Michael Fink 0002