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About A Comparative Analysis of Deep Learning and Machine Learning
This article compares the performance of deep learning and machine learning algorithms for detecting human movement directions using pyroelectric infrared (PIR) sensors. A data acquisition system was implemented using open-source IoT platforms to collect PIR sensor data from 30 subjects. Both classical machine learning and deep learning models were tested on this data to classify movement directions. The results showed that classical machine learning had better performance for real-time detection using initial sensor readings, while a simple deep learning model achieved 90% accuracy even with limited training data from only 3 subjects.
Detailed Information
| Author: | ['şafak erdoğdu'] |
|---|---|
| Publication Year: | 2021 |
| Pages: | 14 |
| Language: | English |
| Format: | |
| Price: | FREE |
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