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An Energy-interference-free Hardware-Software Debugger for Intermittent Energy-harvesting Systems

An Energy-interference-free Hardware-Software Debugger for Intermittent Energy-harvesting Systems

by Sarah Frigg | Apr 2, 2016 | Wireless Communication and Ubiquitous Computing

An Energy-interference-free Hardware-Software Debugger for Intermittent Energy-harvesting Systems   We propose the Energy-interference-free Debugger, a hardware and software platform for energy-interference-free monitoring and debugging of intermittent systems. April...
Assessing Tracking Performance in Complex Scenarios using Mean Time Between Failures

Assessing Tracking Performance in Complex Scenarios using Mean Time Between Failures

by Sarah Frigg | Mar 7, 2016 | Machine Learning, Visual Computing

Assessing Tracking Performance in Complex Scenarios using Mean Time Between Failures   In this work we propose ‘mean time between failures’ as a viable summary of solution quality — especially when the goal is to follow objects for as long as possible March 7,...
Chalkboarding: A New Spatiotemporal Query Paradigm for Sports Play Retrieval

Chalkboarding: A New Spatiotemporal Query Paradigm for Sports Play Retrieval

by Sarah Frigg | Mar 7, 2016 | Machine Learning

Chalkboarding: A New Spatiotemporal Query Paradigm for Sports Play Retrieval   We showcase the efficacy of our approach in a user study, where we demonstrate orders-of-magnitude improvements in search quality compared to baseline systems March 7, 2016Intelligent User...
Person Re-identification using Deformable Patch Metric Learning

Person Re-identification using Deformable Patch Metric Learning

by Sarah Frigg | Mar 7, 2016 | Machine Learning, Visual Computing

Person Re-identification using Deformable Patch Metric Learning   In this paper, we propose to learn appearance measures for patches that are combined using a spring model for addressing the correspondence problem. March 7, 2016IEEE Winter Conference on Applications...
Exploiting View-Specific Appearance Similarities Across Classes for Zero-shot Pose Prediction: A Metric Learning Approach

Exploiting View-Specific Appearance Similarities Across Classes for Zero-shot Pose Prediction: A Metric Learning Approach

by Sarah Frigg | Feb 12, 2016 | Machine Learning, Visual Computing

Exploiting View-Specific Appearance Similarities Across Classes for Zero-shot Pose Prediction: A Metric Learning Approach   We propose a metric learning approach for joint class prediction and pose estimation. February 12, 2016Association for the Advancement of...
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