Adopting Two Supervisors for Efficient Use of Large-Scale Remote Deep Neural Networks - RCR Report

This is the Replicated Computational Results (RCR) Report for our TOSEM paper ”Adopting Two Supervisors Efficient Use of Large-Scale Remote Deep Neural Networks”, where we propose a novel client-server architecture allowing to leverage high accuracy huge neural networks running on remote servers while reducing economical and latency costs typically coming from using such models. As part this RCR, provide replication package, which allows full all results specifically designed facilitate reuse.