In our recent post about receptive field computation, we examined the concept of receptive fields using PyTorch. We learned receptive field is the proper tool to understand what the network 'sees' ...
In a previous post, we had covered the concept of fully convolutional neural networks (FCN) in PyTorch, where we showed how we can solve the classification task using the input image of arbitrary ...
There is a common saying, "A picture is worth a thousand words". In this post, we are going to take that literally and try to find the words in a picture! In an earlier post about Text Recognition, we ...
There are three important parts of Artificial Intelligence Natural Language ProcessingSpeechComputer Vision This post falls in the first category. In this post, we will learn a tool called ...
In this tutorial, we will discuss the various Face Detection methods in OpenCV, Dlib and Deep Learning, and compare the methods quantitatively. We will share code in C++ and Python for the following ...
In the previous two posts, we learned how to use pre-trained models and how to extract features from them for training a model for a different task. In this tutorial, we will learn how to fine-tune a ...
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In 2007, right after finishing my Ph.D., I co-founded TAAZ Inc. with my advisor Dr. David Kriegman and Kevin Barnes. The scalability, and robustness of our computer vision and machine learning algorithms have been put to rigorous test by more than 100M users who have tried our products.
