Part II: Image segmentation

Welcome back to Part II of this series. If you have missed the first part, have a look here: Part I: Image recognition and convolutional backbones.

In this part, you will find a guide through the literature about image segmentation with convolutional neural networks (CNNs) until 2019. It adds none scientific sources to this open access review paper to further increase an intuitive understanding of the evolution of CNNs.

Same as in part one, you can find the tables of the sources in this github repository:

Now, let’s dive into the next chapter of our adventure of deep learning with CNNs. …

Part I: Image recognition and convolutional backbones

The next part of this series is: Part II: Image segmentation

What is this series about

Imagine you wake up and you feel the urge for a data science adventure. You decide to dive in this Deep Learning thing, people are talking about. Great, you switch on your PC to check some state of the art literature before going deep into the endless Github forest to hack around in remote repositories. During your preparations, what might happen is that you stumble across a promising piece of work that tells you that they have used a Triple ResNeXt-101 Cascade Mask R-CNN or something similar…Ahaah…

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Source: imgflip

Your journey might end here, and you return to your cozy cottage, without chests full of shiny algorithms and knowledge you could have shared in your local tavern. …


Thorsten Hoeser

I am a PhD student with a background in geography and data analytics.

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