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Tag Archives: Neural Network

This article is focused on providing an introduction to the AlexNet architecture. Its name comes from one of the leading authors of the AlexNet paper–… Read More
R-CNN: R-CNN was proposed by Ross Girshick et al. in 2014 to deal with the problem of efficient object localization in object detection. The previous… Read More
After the improvement in architecture of object detection network in R-CNN to Fast R_CNN. The training and detection time of the network decrease considerably, but… Read More
Faster R-CNN and YOLO are good at detecting the objects in the input image. They also have very low detection time and can be used… Read More
Before discussing Fast R-CNN, let’s look at the challenges faced by R-CNN The training of R-CNN is very slow because each part of the model… Read More
Inception net achieved a milestone in CNN classifiers when previous models were just going deeper to improve the performance and accuracy but compromising the computational… Read More
We, humans, are very perfect in applying the transfer of knowledge between tasks. This means that whenever we encounter a new problem or a task,… Read More
Let us begin this article with a basic question – “Why padding and strided convolutions are required?” Assume we have an image with dimensions of… Read More
This article will demonstrate how to build a Text Generator by building a Recurrent Long Short Term Memory Network. The conceptual procedure of training the… Read More
Prerequisites: Recurrent Neural Networks  To solve the problem of Vanishing and Exploding Gradients in a Deep Recurrent Neural Network, many variations were developed. One of… Read More
Today, different Machine Learning techniques are used to handle different types of data. One of the most difficult types of data to handle and the… Read More
ADALINE (Adaptive Linear Neuron or later Adaptive Linear Element) is an early single-layer artificial neural network and the name of the physical device that implemented… Read More
Recurrent Neural Network(RNN) are a type of Neural Network where the output from previous step are fed as input to the current step. In traditional… Read More
Convolution is a very important mathematical operation in artificial neural networks(ANN’s). Convolutional neural networks (CNN’s) can be used to learn features as well as classify… Read More
Tensorflow is an open-source machine learning library developed by Google. One of its applications is to developed deep neural networks. The module tensorflow.nn provides support… Read More

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