Samir Brahim Belhaouari
Associate Professor, Hamad Bin Khallifa Uniersity
sbelhaouari [AT] hbku.edu.qa
MADL: A Multilevel Architecture of Deep Learning
Improving CNN Performance with Multilevel Deep Learning Architecture (MADL)
Abstract.
CNN is a powerful tool that is used in many real-life applications. Solving complicated real-life problems requires deeper and larger networks, and hence, a larger number of parameters to optimize. CNN is extended to a multilevel architecture of deep learning (MADL) that breaks down the optimization to different levels and steps where networks are trained and optimized separately. MADL is experimented with using CIFAR-10 and exhibited an improvement of 0.84% compared to a single network resulting in an accuracy of 98.04%.
Illustration of the proposed experimental design.
