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Author: Strahinja Zivkovic

#007 OpenCV projects – Image segmentation with Watershed algorithm

01.12.2020

Highlights: In this post, we are going to cover one of the most important techniques in image processing. We will discuss how to segment an image into different regions. This is an important step in many computer vision applications because it isolates the desired region from the image for further processing tasks. Initially, we will give an overview of the segmentation and start with one of the most common region-based segmentation methods – the Watershed…
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# 005 RNN – Tackling Vanishing Gradients with GRU and LSTM

24.09.2020

Highlights: Recurrent Neural Networks (RNN) are sequence models that are a modern, more advanced alternative to traditional Neural Networks. Right from Speech Recognition to Natural Language Processing to Music Generation, RNNs have continued to play a transformative role in handling sequential datasets. In this blog post, we will carry forward our knowledge from building Language Models to addressing issues that arise from those language models, such as Long-term Dependencies. These can also be termed as…
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#004 RNN – Language Modelling and Sampling Novel Sequences

24.09.2020

Highlights: Recurrent Neural Networks (RNN) are sequence models that are a modern, more advanced alternative to traditional Neural Networks. Right from Speech Recognition to Natural Language Processing to Music Generation, RNNs have continued to play a transformative role in handling sequential datasets. In this blog post, we will learn how RNNs are used to build and train Language Models, and thereby, sample novel sequences from our trained models. By the end of the post, you…
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#003 RNN – Architectural Types of Different Recurrent Neural Networks

24.09.2020

Highlights: Recurrent Neural Networks (RNN) are sequence models that are a modern, more advanced alternative to traditional Neural Networks. Right from Speech Recognition to Natural Language Processing to Music Generation, RNNs have continued to play a transformative role in handling sequential datasets. In this blog post, we will explore the various models and architectural categories of Recurrent Neural Networks. We will learn from real-life cases how these different RNN categories solve day to day problems…
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#002 RNN – Architecture, Mapping, and Propagation

24.09.2020

Highlights: Recurrent Neural Networks (RNN) are sequence models that are a modern, more advanced alternative to traditional Neural Networks. Right from Speech Recognition to Natural Language Processing to Music Generation, RNNs have continued to play a transformative role in handling sequential datasets. In this blog post, we will learn how to build and map a Recurrent Neural Network with some interesting examples. In addition, we will represent basic RNN models using the mathematical notations of…
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