Building Real Time Edge Machine Learning Systems for High Data Rate Acquisition
Author:
Affiliation:
1. Université de Sherbrooke,Interdisciplinary Institute for Technological Innovation - 3IT,Sherbrooke,Québec,Canada
2. Stanford University,SLAC National Accelerator Laboratory,Menlo Park,California,United States of America
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10337770/10337807/10338331.pdf?arnumber=10338331
Reference5 articles.
1. Attosecond time–energy structure of X-ray free-electron laser pulses
2. Potential of edge machine learning for instrumentation
3. A survey of machine learning to fpga tool-flows for instrumentation;Rahimifar
4. Combining optimized quantization and machine learning for real-time data reduction at the edge;Gouin-Ferland
5. Fast convolutional neural networks on FPGAs with hls4ml
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