ELITE: Enabling Learning and Inferring compact deep neural network Topologies on Edge devices

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Project description:

The primary goal of the project “ELITE: Enabling Learning and Inferring compact deep neural network Topologies on Edge devices” is to investigate new ways to build compact DNNs from scratch by 1) using efficient latent representations and their factors of variations and 2) exploiting NAS based techniques for minimal deep architectural design. The final objective is to construct compact DNN models suitable for edge devices for space missions. 

  • Starting date: 01/09/2022
  • Duration: 36 months + 12
  • Funding source: FNR CORE
  • Researchers: Prof. Djamila Aouada, Dr. Enjie Ghorbel, Dr. Michele Jamrozik, Peyman Rostami
  • Partners: LMO, Melbourne Space Laboratory (MSL) at University of Melbourne