In embedded systems image classification with convolutional Neural Network
Deep Neural Network is successfully applied for image classification problems. The understanding of what object is detected in the image is great interested. The prupose of this article is that image classification problem could be applied in real time systems. In this article we propose a CNN architecture for Cifar 10 dataset. This article is shown that with 2GB memory real time system achieves %85.8 accuracy for image classification.
2018 26th Signal Processing and Communications Applications Conference (SIU)