In this blog post, we will learn to create a TensorFlow Lite model using the TF Lite Model Maker Library. We will fine-tune a pre-trained image classification model on the custom dataset and ...
The recent trend in the development of larger and larger Deep Learning models for a slight increase in accuracy raises the concern about their computational efficiency and wide scaled usability. We ...
Introduction Super-resolution refers to the process of upscaling or improving the details of the image. Follow this blog to learn the options for Super Resolution in OpenCV. When increasing the ...
In many of our previous posts, we used OpenCV DNN Module, which allows running pre-trained neural networks. One of the module's main drawback is its limited CPU-only inference use since it was ...
In this blog post, we will be installing OpenCV on Windows for C++ and Python. The C++ installation is done with the help of custom setup exe files. Whereas Python installation is done with ...
In this post, we will discuss about two Deep Learning based approaches for motion estimation using Optical Flow. FlowNet is the first CNN approach for calculating Optical Flow and RAFT which is the ...
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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.
