Depth estimation is a critical task for autonomous driving. It's necessary to estimate the distance to cars, pedestrians, bicycles, animals, and obstacles.The popular way to estimate depth is LiDAR. ...
Classification with Localization: Convert any Keras Classifier to a Detector
Image classification is used to solve several Computer Vision problems; right from medical diagnoses, to surveillance systems, on to monitoring agricultural farms. There are innumerable ...
Image Classification with OpenCV for Android
In the previous post, we've learned how to work with OpenCV Java API with the example of a PyTorch convolutional neural network, integrated into the Java pipeline. Now we are going to transform ...
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 ...
