COMBINING COMPRESSION, PARTITIONING AND QUANTIZATION OF DL MODELS FOR FITMENT IN HARDWARE PROCESSORS

Small and compact Deep Learning models are required for embedded AI in several domains. In many industrial use-cases, there are requirements to transform already trained models to ensemble embedded systems or re-train those for a given deployment scenario, with limited data for transfer learning. Mo...

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Bibliographische Detailangaben

Hauptverfasser:	Dey, Swarnava, Swain, Amit, Kulkarni, Gitesh, Bhaumik, Chirabrata, Mukherjee, Arijit, Tyagi, Aakash, Pal, Arpan, Ukil, Arijit, Mondal, Jayeeta, Sahu, Ishan
Format:	Patent
Sprache:	eng ; fre ; ger
Schlagworte:	CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING PHYSICS
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