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Title: Resource-Efficient Computing in Wearable Systems
We propose two optimization techniques to minimize memory usage and computation while meeting system timing constraints for real-time classification in wearable systems. Our method derives a hierarchical classifier structure for Support Vector Machine (SVM) in order to reduce the amount of computations, based on the probability distribution of output classes occurrences. Also, we propose a memory optimization technique based on SVM parameters, which results in storing fewer support vectors and as a result requiring less memory. To demonstrate the efficiency of our proposed techniques, we performed an activity recognition experiment and were able to save up to 35% and 56% in memory storage when classifying 14 and 6 different activities, respectively. In addition, we demonstrated that there is a trade-off between accuracy of classification and memory savings, which can be controlled based on application requirements.  more » « less
Award ID(s):
1750679
PAR ID:
10141794
Author(s) / Creator(s):
; ; ; ;
Date Published:
Journal Name:
2019 IEEE International Conference on Smart Computing (SMARTCOMP 2019)
Page Range / eLocation ID:
150 to 155
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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