PyTorch
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
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
In this post, we will learn how to convert a PyTorch model to TensorFlow. If you are new to Deep Learning you may be overwhelmed by which framework to use.
Stanford ML Group, led by Andrew Ng, works on important problems in areas such as healthcare and climate change, using AI. Last year they released a knee MRI dataset consisting
The foreground is the part of a view or picture, that is nearest to you when you look at it (Oxford dictionary). We, humans, are usually good at distinguishing foreground
In this post, we continue to consider how to speed up inference quickly and painlessly if we already have a trained model in PyTorch. In the previous post We discussed
