Verfahren und System zur Partitionierung eines Tiefen Faltenden Netzwerks zur Ausführung auf Rechnerbeschränkten Vorrichtungen

Details

Veröffentlichungs-Nr.

EP3648013

Aktenzeichen

EP19189580

Anmeldetag

1. August 2019

Veröffentlichung

27. November 2024

Erteilung

27. November 2024

Rechtsraum

EP

IPC

G06N3/08G06N3/045G06N3/04// G06N3/063

Abstract

A growing need for inferencing to be run on fog devices exists, in order to reduce the upstream network traffic. However, being computationally constrained in nature, executing complex deep inferencing models on such devices has been proved difficult. A system and method for partitioning of deep convolution neural network for execution of computationally constraint devices at a network edge has been provided. The system is configured to use depth wise input partitioning of convolutional operations in deep convolutional neural network (DCNN). The convolution operation is performed based on an input filter depth and number of filters for determining the appropriate parameters for partitioning based on an inference speedup method. The system uses a master-slave network for partitioning the input. The system is configured to address these problems by depth wise partitioning of input which ensures speedup inference of convolution operations by reducing pixel overlaps.

Anmelder

Firma

Tata Consultancy Services Limited

Land

🇮🇳 Indien

Fachgebiete