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End-to-end deep learning inference with CMSSW via ONNX using docker
Deep learning techniques have been proven to provide excellent performance for a variety of high-energy physics applications, such as particle identification, event reconstruction and trigger operations. Recently, we developed an end-to-end deep learning approach to identify various particles using...
Autores principales: | Chaudhari, Purva, Chaudhari, Shravan, Chudasama, Ruchi, Gleyzer, Sergei |
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Lenguaje: | eng |
Publicado: |
2023
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Materias: | |
Acceso en línea: | http://cds.cern.ch/record/2872502 |
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