Hello, all! I hope you got excited by the title itself. What if I tell you that building a face recognition system is not so difficult? Yes, it is, and of course very exciting. Let’s build a complete face recognition system which enables you to enroll a new candidate into the system and perform recognition with higher accuracy!
Ever wondered, how does the Google reverse image search engine works which take in an image and returns you the most similar images in a fraction of a second? How does the Pinterest let you search the visually similar images of the selected objects? Sounds interesting? Do you want to understand and build similar kind of a system? If yes then you are at the right place. Continue reading
In this post we will be implementing two simple Recurrent Neural Networks (RNN) one for classification and the other for regression tasks.
Classification using RNN
It takes in a binary number and returns the XOR of the number. For example if the input is
10110 then it should output
11011, as Continue reading
In the last post we discussed how to extract the sudoku region from the captured frame of a live stream and then we applied perspective transform to the extracted region and then we slide a window through each cell and recognized the digits in the cells. Now in this post we discuss how to solve the sudoku puzzle using Backtracking algorithm. There are several approaches to solve the sudoku puzzle. For example, you can find some of them in this paper.
Though there are several approaches to solve it, let’s stick to the traditional backtracking algorithm to solve the puzzle. For our understanding, just have a look at how the sudoku is presented below.