Crime scene prediction by detecting threatening objects using convolutional neural network

Abstract

Crime scene prediction without human intervention can have outstanding impact on computer vision. In this paper, we present CNN in the use of detect knife, blood and gun in order to reach a prediction whether a crime has occurred in a particular image. We emphasized on the accuracy of detection so that it hardly gives us wrong alert to ensure efficient use of the system. This paper use Non linearity ReLu, Convolutional Neural Layer, Fully connected layer and dropout function of CNN to reach a result for the detection. We use Tensorflow open source platform to implement CNN to achieve our expected output. This system can achieve the test accuracy of 90.2 % for the data sets we have that is very much competitive with other systems for this particular task.