Paper Title
Brain Tumour Detection Using Deep Convolutional Neural Network

Abstract
The idea of CNN is A tumor is nothing but excess cells growing in an uncontrolled manner. Brain tumor cells grow in a way that they eventually take up all the nutrients meant for the healthy cells and tissues, which results in brain failure. Currently, doctors locate the position and the area of brain tumor by looking at the MR Images of the brain of the patient manually. This results in inaccurate detection of the tumor and is considered very time consuming. A Brain Cancer is very critical disease which causes deaths of many individuals. The brain tumor detection and classification system is available so that it can be diagnosed at early stages. Cancer classification is the most challenging tasks in clinical diagnosis. The classification of brain tumors is one of the most significant and difficult problems to solve. As a result of the fact that manual classification with the assistance of humans might result in incorrect diagnoses and forecasts. In addition to this, whenever there is a substantial amount of information that must be processed manually, the process develops into a lengthy activity that is difficult to complete. As a result of the fact that brain tumors can take on a wide variety of forms, as well as the fact that there is a certain degree of similarity among normal and tumor tissues, it can be challenging to distinguish sections of a patient's brain that contain tumors from scans of that brain. Keyword - Classification, Diagnosis, Brain Cancer, Brain Tumor