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Low-Cost Outdoor Air Quality Monitoring and Sensor Calibration: A Survey and Critical Analysis
Periodic re-calibration can improve the accuracy of low-cost sensors, particularly with machine-learning-based calibration, which has shown great promise due to its capability to calibrate sensors in-field.
Towards Using Unlabeled Data in a Sparse-coding Framework for Human Activity Recognition
We propose a sparse-coding framework for activity recognition in ubiquitous and mobile computing that alleviates two fundamental problems of current supervised learning approaches.
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