There are 50000 training images and 10000 test images. To classify those 10 classes of images a convolutional neural network (CNN) is used here. CNN achieved 85.0% accuracy in the test dataset. The ...

In this article, we will implement the multiclass image classification using the VGG-19 Deep Convolutional Network used as a Transfer Learning framework where the VGGNet comes pre-trained on the ...

DoT-Net is a multiclass classifier that can effectively identify document component blocks such as text, image, table, mathematical expression, and line-diagram, whereas most related methods have ...

The Intrusion Detection System (IDS) is designed to detect cyberattacks. However, given the vast number of alerts generated by IDS for different registered attack signatures, there's a growing demand ...

Image Classification using CNN on FPGA Project is about designing a Trained Neural n/w (CIFAR-10 dataset) on FPGA to classify an Image I/P using deep-learning concept (CNN- Convolutional Neural ...