Quick & Lightweight Tuberculosis Detection:A CNN Based Approach

Abstract

In current scenario Convolutional Neural Network (CNN) has gained the attention of the researchers. It is a special type of feed forward neural network used to handle large images. It has the capability of adjusting the parameters. However, it is computationally expensive as it takes more training time. So in this paper we are interested to propose a new technique which will reduce the number of training parameters of CNN as well as providing a promising accuracy. The proposed technique is validated for the detection of tuberculosis.