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A picture is worth a thousand words! As computer vision and machine learning experts, we could not agree more. Human intuition is the most powerful way of making sense out

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 input

Let’s play rock, paper scissors. You think of your move and I’ll make mine below this line in 1…2…and 3. I choose ROCK. Well? …who won. It doesn’t matter cause

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

Raspberry Pi is a small ARM computer with a camera, a network controller, and Linux on board. That makes it a good choice for DIY computer vision projects. In this

The life of a machine learning engineer consists of long stretches of frustration and a few moments of joy! First, struggle to get your model to produce good results on

In an earlier post, we covered the problem of Multi Label Image Classification (MLIC) for Image Tagging. Recall that MLIC is an image classification task but unlike multi-class image classification

This is a a gentle introduction to federated learning — a technique that makes machine learning more secure by training on decentralized data. We will also cover a real-life example

Wouldn’t it be cool if you could just wave a pen in the air to draw something virtually and it actually draws it on the screen? It could be even

Imagine, one day you have an amazing idea for your machine learning project. You write down all the details on a piece of paper- the model architecture, the optimizer, the

In the previous post, we learned how to apply a fixed number of tags to images. Let’s now switch to this broader task and see how we can tackle it. 

We all remember those awesome childhood days when we use to go to amusement parks or county fairs. One of my favorite elements of these amusement parks was the fun-house

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