Results For: neural networks

When dealing with image data in deep learning, then convolutional neural networks (CNN) are the go-to architectures. Convolutional neural networks have proved to provide many state-of-the-art solutions and benchmarks in deep learning and computer vision. Image recognition, object detection, and semantic segmentation are only some of the applications of convolutional neural networks among many more. […] ...

In this article, we will get hands-on experience on how to build robust deep neural networks by adding noise to the input data. One of my previous articles was Adding Noise for Robust Deep Neural Network Models. It explained how neural networks suffer while generalizing when we add noise to the data. And how we […] ...

In this tutorial, we are going to learn how to carry out image classification using neural networks in PyTorch. Basically, we will build convolutional neural network models for image classification. This is the fourth part of the series, Deep Learning with PyTorch.Part 1: Installing PyTorch and Covering the Basics.Part 2: Basics of Autograd in PyTorch.Part 3: Basics of Neural Network in PyTorch. Part […] ...

Computer Vision and Deep Learning together have given some novel solutions to many of the real world problems. And automatic traffic sign recognition is one of them. Recognizing traffic signs is one of the most important aspects when considering road safety and automated driving. Manual detection, classification, and hard coding are not possible when visualizing […] ...

Convolutional Neural Network (CNN for short) is perhaps the most widely used deep learning model when it comes to computer vision application. In this article, you will get to know about the basic working principle of convolutional neural networks. The Building Block of a CNN Convolutional Neural Networks are pretty widely used nowadays for image-classification […] ...