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# 019 Siamese Network in PyTorch with application to face similarity

07.11.2021

Highlights: Hello and welcome back. In today’s post, we’ll discuss and learn a very interesting neural network architecture. We will discuss Siamese Neural Networks, whose goal is to calculate a similarity between two given images. For example, it should tell us how similar two faces are. Siamese networks were first introduced in the early 1990s by Bromley and LeCun[1] to solve signature verification as an image matching problem It is a very popular solution when it comes…
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#003 Advanced Computer Vision – Multi-Task Cascaded Convolutional Networks

25.10.2021

Highlights: Face detection and alignment are correlated problems. Change in various poses, illuminations, and occlusions in unrestrained environments can make these problems even more challenging. In this tutorial, we will study how deep learning approaches can be great performing solutions for these two problems. We will study a deep cascaded multi-task framework proposed by Kaipeng Zhang [1] et al. that predicts face and landmark location in a coarse-to-fine manner. So let’s get started! Tutorial Overview:…
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#014 Calculating Sparse Optical flow using Lucas Kanade method

31.05.2021

Highlights: In this post, we will show how we can detect moving objects in a video using the Lucas Kanade method. This approach is based on tracking a set of distinctive feature points. Therefore, it is also known as a Sparse Optical Flow method. We will give a detailed theoretical understanding of the Lucas Kanade method and show how it can be implemented in Python using OpenCV. Tutorial overview: Understanding the Concept of Motion Optical…
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#009 PyTorch – How to apply Backpropagation With Vectors And Tensors

18.01.2021

Highlights: In Machine Learning, a backpropagation algorithm is used to compute the loss for a particular model. The most common starting point is to use the techniques of single-variable calculus and understand how backpropagation works. However, the real challenge is when the inputs are not scalars but of matrices or tensors. In this post [1], we will learn how to deal with inputs like vectors, matrices, and tensors of higher ranks. We will understand how…
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#006 PyTorch – Solving the famous XOR problem using Linear classifiers with PyTorch

13.01.2021

Highlights: One of the most historical problems in the Neural Network arena is the classic XOR problem where predicting the output of the ‘Exclusive OR’ gate becomes increasingly difficult using traditional linear classifier methods. In this post, we will study the expressiveness and limitations of Linear Classifiers, and understand how to solve the XOR problem in two different ways. So let’s begin.   Tutorial Overview: Logistic Regression Model Simple Logical Boolean Operator Problems The OR…
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Learn how to align Faces in OpenCV in Python

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