You use panorama mode to click a wide-view photo in your camera. But how does this panorama mode actually work under the hood? Or suppose you have an unstable video of your bike riding, and you go to ...
t-SNE: T-Distributed Stochastic Neighbor Embedding Explained
Visualizing training data is often essential to design a good Machine Learning model. However, generally feature dimensions are much more than three. So to get visual insight, dimensionality reduction ...
Otsu’s Thresholding with OpenCV
In this post, we will examine Otsu's method for automatic image thresholding. What is Image Thresholding? Image thresholding is used to binarize the image based on pixel intensities. The ...
CNN Receptive Field Computation Using Backprop with TensorFlow
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' ...
CNN Fully Convolutional Image Classification (FCN CNN) with TensorFlow –
In a previous post, we covered the concept of fully convolutional neural networks (FCN) in PyTorch, where we showed how we could solve the classification task using the input image of arbitrary ...
Faster R-CNN Object Detection with PyTorch
1. Image Classification vs. Object Detection Image Classification is a problem where we assign a class label to an input image. For example, given an input image of a cat, the output of an image ...
