Millimetre Wave Receiver of Radar Detection with Deep Learning for ADAS Edge Computing Vision
| Autor: | Wen-Cheng Lai, Yi-Jiun Hung, Hui-Chiao Chen, Ting-Jia Guo, Yu-Kai Zhang |
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| Rok vydání: | 2020 |
| Předmět: |
business.industry
Computer science Pedestrian detection Deep learning ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION 020206 networking & telecommunications Advanced driver assistance systems 02 engineering and technology Convolutional neural network Parallel processing (DSP implementation) Extremely high frequency 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Artificial intelligence business Throughput (business) Edge computing Computer hardware |
| Zdroj: | 2020 15th International Microsystems, Packaging, Assembly and Circuits Technology Conference (IMPACT). |
| Popis: | This article introduces integrated millimeter wave receiver of radar detection with deep learning, performance optimization and low power dissipation. The proposed pedestrian detection system (PDS) on embedded platform used as edge computing vision for advanced driver assistance systems (ADAS). The proposed millimeter wave receiver can reduce image amount of calculation with featured object and enhance throughput with parallel processing on deep convolutional layer of ARM Neon to comparison with produce MobileNet and traditional convolutional neural network (CNN). |
| Databáze: | OpenAIRE |
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