Abstract
Abstract: Lung cancer ranks among the primary causes of death on global scale. Catching this disease early can increase your chances or opportunities of survival. Computer-assisted detection (CAD) is used to create CT images and even X-rays of the lungs to determine whether cancer is present in the images. This paper represents an image classification by the combination of a neural network (CNN) algorithm and support vector machine (SVM). The algorithm spontaneously separates and analyzes lung picture or image to detect cancer cells. Compared to full-scale networks, CNNs are easier to train and have less overhead. We introduce CNN-SVM because it has accurate performance than other existing terminologies. The merits of this method are that it can detect cancer on the CT image
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