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Before the deep learning revolution redefined computer vision, Haar features and Haar cascades were the tools you must not ignore for object detection. Even today, they are very useful object detectors because they are lightweight. In this post, you will learn about the Haar cascade and how it can detect objects. After completing this post, …
The Random Forest algorithm forms part of a family of ensemble machine learning algorithms and is a popular variation of bagged decision trees. It also comes implemented in the OpenCV library. In this tutorial, you will learn how to apply OpenCV’s Random Forest algorithm for image classification, starting with a relatively easier banknote dataset and …
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The Naive Bayes algorithm is a simple but powerful technique for supervised machine learning. Its Gaussian variant is implemented in the OpenCV library. In this tutorial, you will learn how to apply OpenCV’s normal Bayes algorithm, first on a custom two-dimensional dataset and subsequently for segmenting an image. After completing this tutorial, you will …
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In a previous tutorial, we have explored the use of the Support Vector Machine algorithm as one of the most popular supervised machine learning techniques that comes implemented in the OpenCV library. So far, we have seen how to apply Support Vector Machines to a custom dataset that we have generated, consisting of two-dimensional points …
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One of the pre-processing steps that are often carried out on images before feeding them into a machine learning algorithm is to convert them into a feature vector. As we will see in this tutorial, there are several advantages to converting an image into a feature vector that makes the latter more efficient. Among the …
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Sponsored Content By Rajan Mistry Sr. Applications Engineer with the Qualcomm Developer Network Today, you can’t help but read the media headlines about AI and the growing sophistication of generative AI models like Stable Diffusion. A great example of a use case for generative AI on Windows is Microsoft 365 Copilot. This AI assistant can …
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The Support Vector Machine algorithm is one of the most popular supervised machine learning techniques, and it comes implemented in the OpenCV library. This tutorial will introduce the necessary skills to start using Support Vector Machines in OpenCV, using a custom dataset that we will generate. We will then apply these skills for the specific …
In the previous post, you saw that OpenCV can extract features from an image using a technique called the Histogram of Oriented Gradients (HOG). In short, this is to convert a “patch” of an image into a numerical vector. This vector, if set up appropriately, can identify key features within that patch. While you can …
Read more “How to Train a Object Detection Engine with HOG in OpenCV”
At the very start of your machine learning journey, making use of publicly available datasets alleviates the worry of having to create the datasets yourself, and rather lets you focus on learning to use the machine learning algorithms. It also helps if the datasets are moderately sized and do not require too much pre-processing, to …
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The structure of Ghostbuster, our new state-of-the-art method for detecting AI-generated text. Large language models like ChatGPT write impressively well—so well, in fact, that they’ve become a problem. Students have begun using these models to ghostwrite assignments, leading some schools to ban ChatGPT. In addition, these models are also prone to producing text with factual …
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