Hierarchical Image Classification on Bayesian Cascade Neural Learning
M Dharmalingam, G.D. Praveenkumar · Zenodo (CERN European Organization for Nuclear Research) · 2020
The performance of image classification on Bayesian cascade neural learning techniques using in coarse and fine layer in LSTM. Recurrent Neural Network (RNN) system experience from Vanishing Gradient (VG) issues. The Gradients needs to proliferate down through numerous layers of the Recurrent Neural Network (RNN).So we integrate the LSTM do not go through from vanishing gradient problem that forward layer. It support different number of layers in Convolutional Neural Network (CNN) is designed for image classification. The Long Short Term Memory (LSTM) processed with Bayesian Cascade Neural Learning (BCNL) with CNN of GoogleNet framework to designed the hierarchical image classification. The elasticity of LSTM model to computed hierarchical label on standard dataset of CIFAR-100.