Dropout technique for image classification based on extreme learning machine
Gangi Siva Nandini, A. P. Siva Kumar, K Chidananda
Abstract
An extreme learning machine is a feed-forward neural network is a feature learning method used in image classification efficiently because of the faster learning rate, speed, good generalization ability, ease of implementation, and efficiency in classifications. This paper presents a new model for the classification of images by using an extreme learning machine classifier which works in two stages using deep learning techniques. A new framework is built by using the dropout technique of CNN for classifying images with less training time and also no need to over train neurons. The proposed model has a high accuracy of 98% using 1000 images. The proposed paper accomplishes the best results in image classification compare with other related methods on image classification.