Track: Modeling and Simulation
Abstract
Optimizers are approaches or algorithms dependent to enhance the characteristics of the Neural Network
(NN) like weights and learning rate in order to decrease the loss rate, On the other hand, Siamese Neural
Network (SNN) are two identical sub-networks, they work in parallel and they are sharing parameters and
weight, SNN uses for indicate similarity. In this research, we study the effect of optimizers Siamese Neural
Network, using Digits handwritten (MINST) dataset, the effects is studied for Adam, Nadam, Adadelta and
SGD optimizers with respect to process time and accuracy, the accuracy is 97%, 97%, 79% and 92%.
Keywords
Deep learning, Siamese Network, Image classification, CNN, Adam, Adadelta, SGD,Nadam