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Object detection is a large field in computer vision, and one of the more important applications of computer vision "in the wild". From it, instance segmentation was extracted, and is tasked with having models predict not only the label and bounding box of an object, but also the...
David Landup
Edge detection is something we do naturally, but isn't as easy when it comes to defining rules for computers. While various methods have been devised, the reigning method was developed by John F. Canny in 1986., and is aptly named the Canny method. It's fast, fairly robust, and works just...
The Adapter Design Pattern is a popular Structural Design Pattern used in software engineering. This guide looks at how we can implement the Adapter Design Pattern in Python. Design Patterns are template-like solutions - practically recipes for solving recurring, common problems in software development. The Adapter Pattern is based upon...
Guest Contributor
Thresholding is a simple and efficient technique to perform basic segmentation in an image, and to binarize it (turn it into a binary image) where pixels are either 0 or 1 (or 255 if you're using integers to represent them). Typically, you can use thresholding to perform simple background-foreground segmentation...
The learning rate is an important hyperparameter in deep learning networks - and it directly dictates the degree to which updates to weights are performed, which are estimated to minimize some given loss function. In SGD: $$ weight_{t+1} = weight_t - lr * \frac{derror}{dweight_t} $$ With a learning...
Improving the performance of a training loop can save hours of computing time when training machine learning models. One of the ways of improving the performance of TensorFlow code is using the tf.function() decorator - a simple, one-line change that can make your functions run significantly faster. In this...
Felipe Antunes
Data augmentation has, for a long while, been serving as a means of replacing a "static" dataset with transformed variants, bolstering the invariance of Convolutional Neural Networks (CNNs), and usually leading to robustness to input. Note: Invariance boils down to making models blind to certain perturbations, when making...
A dictionary in Python is a collection of items that stores data as key-value pairs. In Python 3.7 and later versions, dictionaries are sorted by the order of item insertion. In earlier versions, they were unordered. In this article, we'll take a look at how we can sort a...
Naazneen Jatu
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