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Showing posts from July 14, 2020

A Convolution Neural Network Application

Hello guys, welcome to this new project. In this project you will learn about Convolutional Neural Networks and the project is to Detect You whenever you are in-front of your laptop. One thing I want to conform before starting our project, this project is totally different from face detection. I will discuss about face detection in another session. And guys don't worry about code. 'Why worry, when we have Google's Tensorflow!'.You can find the code here , have a look. OK guys lets start our project.  Convolution Neural Network Convolution Neural Network(CNN) Why CNNs? Let us start the session from this question - Why CNNs? We have DNN(Deep Neural Networks) which performs well on images but why CNNs? To know the reason, let us assume we have an RGB image of shape (64,64,3). This has 12288 (64*64*3) number of pixels (It is also called as 12288 Dimensional feature vector).It is not too bad! But as technology increased we can find images of (1000,1000,3) that has nearly 3 M

Hand Signs Using KNN

Hello guys, welcome to this new project named "Hand Signs using KNN". There are different types of Hand Signs, but here we use only hand signs of  Zero, One, Two, Three, Four & Five. But wait.! we are not using any Deep Learning or Neural Networks in this project. Instead we are using KNN a.k.a K-Nearest Neighbor which is one the Machine Learning Algorithms. We will talk about this later in this post. But how can we give directly images as input to the model, if we use a Machine Learning algorithm? Don't worry about it there are two files (train.h5, test.h5) that consists of features of the images (here features is nothing but pixel values of the image). You can find these files and also full code  here . Hand Signs Now lets talk about K Nearest Neighbor. K Nearest Neighbor(A Supervised Learning Algorithm) Introduction KNN algorithm is the laziest algorithm , we can also say KNN as instance based learning. It is called as the laziest algorithm because   it does nothin