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
Creating a custom object detector was a challenge, but not now. There are many approaches for handling object detection. Of all, Haarcascades and HOG+SVM are very popular and best known for their performance. Though Haarcascades which were introduced by Viola and Jones are good in achieving decent accuracy, HOG+SVM proved to outperform the Haarcascades implementation. Here in this post we are going to build a object detector using HOG+SVM model. The output from our detector is something similar as shown below.