| scholarly article | Q13442814 |
| P8978 | DBLP publication ID | journals/sensors/MauldinCMNR18 |
| P356 | DOI | 10.3390/S18103363 |
| P932 | PMC publication ID | 6210545 |
| P698 | PubMed publication ID | 30304768 |
| P50 | author | Vangelis Metsis | Q114959166 |
| P2093 | author name string | Anne H H Ngu | |
| Coralys Cubero Rivera | |||
| Marc E Canby | |||
| Taylor R Mauldin | |||
| P2860 | cites work | Human fall detection on embedded platform using depth maps and wireless accelerometer. | Q51026125 |
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| P275 | copyright license | Creative Commons Attribution 4.0 International | Q20007257 |
| P6216 | copyright status | copyrighted | Q50423863 |
| P4510 | describes a project that uses | deep learning | Q197536 |
| P433 | issue | 10 | |
| P407 | language of work or name | English | Q1860 |
| P921 | main subject | deep learning | Q197536 |
| P577 | publication date | 2018-10-09 | |
| P1433 | published in | Sensors | Q3478643 |
| P1476 | title | SmartFall: A Smartwatch-Based Fall Detection System Using Deep Learning | |
| P478 | volume | 18 |
| Q90190749 | A Study on the Application of Convolutional Neural Networks to Fall Detection Evaluated with Multiple Public Datasets |
| Q64070007 | Accelerometer-Based Human Fall Detection Using Convolutional Neural Networks |
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| Q89862245 | Resource Usage and Performance Trade-offs for Machine Learning Models in Smart Environments |
| Q93079074 | Robust Self-Adaptation Fall-Detection System Based on Camera Height |
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