OpenCV library is widely used due to its extensive coverage of the computer vision tasks, and availability to involve it in various projects, including deep learning. Usually, OpenCV is used with C++ ...
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 ...
This post explains the implementation of Support Vector Machines (SVMs) using Scikit-Learn library in Python. We had discussed the math-less details of SVMs in the earlier post. In this post, we ...
Ideas in Machine Learning have a "winner takes all" quality. When an idea takes off, it dominates the field so completely that one tends to believe it is the only idea worth pursuing. Today, Deep ...
In our previous tutorial, we learned how to use models which were trained for Image Classification on the ILSVRC data. In this tutorial, we will discuss how to use those models as a Feature Extractor ...
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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.
