Abstract
Object detection from repository of images is challenging task in the area of computer vision and image processing in this work we present object classification and detection using cifar-10 data set with intended classification and detection of airplain images. So we used convolutional neural network on keras with tensorflow support the experimental results shows the time required to train, test and create the model in limited computing system. We train the system with 60,000 images with 25 epochs each epoch is taking 722to760 seconds in training step on tensorflow cpu system. At the end of 25 epochs the training accuracy is 96 percentage and the system can recognition input images based on train model and the output is respective label of images.
Published Version
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