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Tag: machine learning

# 020 Overview of Semantic Segmentation methods

08.11.2021

Highlights: Hello and welcome back. In this post, we will see how we can use Neural Networks for the segmentation task. To be more precise, it will be about Semantic Segmentation. The goal of Semantic Segmentation is to label each pixel of an image with a corresponding class. We will cover some of the most popular Deep Learning models for segmentation: Fully Convolutional Neural Network SegNet U-Net Tutorial Overview: What is Semantic Segementation? Types of segmentations Fully Convolutional Neural…
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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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#017 Face detection algorithms comparison

01.06.2020

Highlights: Researchers and computer vision practitioners have generally developed many face detection algorithms. In this post, we will use 5 of the most popular algorithms. Also, we will compare their detection accuracy rate. Additionally, we will measure the runtime of these algorithms. Facial detection is a technique used by computer algorithms to detect a person’s face through images. Accordingly, the objective of facial detection is to get different features of human faces from images. Due to…
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Holopix50k: A Large-Scale In-the-wild Stereo Image Dataset

28.03.2020

A team of Computer vision researchers at Leia Inc. have released a large-scale database of 49,368 (~50k) stereoscopic image pairs collected from the popular Lightfield social media app Holopix™. This is the largest dataset of stereoscopic image pairs ever released publicly that contain in-the-wild scenarios captured from mobile phones. For context, the second-largest dataset in this category consists of only 1024 stereoscopic image pairs, almost 50 times less! The dataset is available for download immediately…
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#004 Linear Algebra – The determinant

23.03.2020

Highlight: In this post we will explain what the determinant is and why we use it in linear algebra. We will give an interpretation of a determinant both in a 2-D and in a 3-D space. Also, we will show how to implement these calculations in Python. Tutorial Overview: Determinant in a 2-D coordinate system Determinant in a 3-D coordinate system 1. Determinant in a 2-D coordinate system In the previous post we saw how…
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