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Tag Archives: Neural Network

DeepFace is the facial recognition system used by Facebook for tagging images. It was proposed by researchers at Facebook AI Research (FAIR) at the 2014… Read More
FaceNet is the name of the facial recognition system that was proposed by Google Researchers in 2015 in the paper titled FaceNet: A Unified Embedding… Read More
To specify the architecture of a neural network with all layers connected sequentially, create an array of layers directly. To specify the architecture of a… Read More
We know that our world is changing quickly but there are lot of concrete technology advances that you might not hear a lot about in… Read More
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 data. One of the most difficult type of data to handle and forecast is… Read More