The field of computer vision has existed since the late 1960s. Image classification and object detection are some of the oldest problems in computer vision that researchers have tried to solve for ...
RAFT: Optical Flow estimation using Deep Learning
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 ...
Image Classification with OpenCV Java
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++ ...
PyTorch to Tensorflow Model Conversion
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. We personally think PyTorch is the first ...
Stanford MRNet Challenge: Classifying Knee MRIs
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 of 1,370 knee MRI ...
Image Matting with state-of-the-art Method “F, B, Alpha Matting”
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 objects on images from the ...