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Last updated: Feb 7, 2022

Convolution Neural Network

Convolution Neural Network (CNN) is a sophisticated deep learning algorithm that works best with images. It classifies images based on their various features. Because it is a deep learning algorithm, it can learn and implement at various stages of training.
Understanding of Convolutional Neural Network
The objective of this blog is to understand the Convolution Neural Network.
Padding in Convolutional Neural Network MEDIUM
This article discusses the padding in convolutional neural network in detail. It also discusses the need for padding and its use cases.
Author Alisha
Convolution Layer
In this blog, we’ll see what convolution is and how to build a simple convolutional neural network to classify MNIST Digits.
Stride in Convolutional Neural Network (CNN) MEDIUM
Discover how stride impacts convolutional neural networks (CNNs). This article will cover topics like Stride in convolutional neural network, differences between stride and padding, and the effects of stride.
Pooling Layer in Convolutional Neural Network MEDIUM
This article discusses the Pooling Layer in Convolutional Neural Networks.
Convolution layer, Padding, Stride, and Pooling in CNN
The objective of this blog is to understand various layers of Convolution Neural Networks.
This article covers the concept of usage of GPUs(Graphics Processing Units) in CNN(Convolutional Neural Networks).
Convolutional Neural Network in Keras
In this blog, we will see the implementation of Convolutional neural networks using Keras.
Data Augmentation
In this blog, we discussed data augmentation, sample model, horizontal and vertical augmentation followed by brightness augmentation.
Softmax and Cross-Entropy EASY
This article will study softmax function and cross-entropy with their implementation. Further, we will see why cross-entropy is used with the softmax function.
VGG-16 - CNN Model EASY
This blog will provide you with an overview of the VGG-16 and illustrate it using an object detection use-case.
In this article, we will learn about the architecture of the AlexNet with implementation. Important terminologies that are needed to build the AlexNet architecture.
Classic ConvNet Architectures HARD
This article discusses the different Classic ConvNet architectures with detailed explanations.
Author Alisha
This blog focuses on the approach and architecture of ZFNet
VGG Network EASY
VGG, a classic convolutional neural network (CNN) architecture discussed in this blog.
This blog aims to explain what inceptionNet is and elucidate the evolution of its versions.
ResNet Architecture EASY
This article focuses on the concept, need, architecture, and implementation of ResNet.
GoogLeNet Model EASY
This article discusses googlenet architecture, features of google net architecture, and advantages of google net with faqs.
Visualizing Convolutional Neural Networks with Filters
This blog explains the convolutional neural network. In detail, we will discuss how to enter visualizations in CNN, visualize convolutional layers, pre-fit the VGG model, how to visualize filters, and many more.
Author Aditi
Guided Backpropagation
In this article, we will discuss guided backpropagation, use of guided backpropagation along with an example and a code implementation of it.
Fooling Convolutional Neural Network
This blog will focus on the basics behind the fooling of Convolution neural networks. Let's begin.
Dense In Deep Learning EASY
This article will focus on the denser layer in neural networks, different hyperparameters of Keras dense layer, and finally, a basic implementation.