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Check out the latest superpixel benchmark — Superpixel Benchmark (2016) — and let me know your opinion! @david_stutz

ARTICLE

Reviews and Rebuttal for “Superpixels: An Evaluation of the State-of-the-Art”

This article summarizes the reviews corresponding to our paper “Superpixels: An Evaluation of the State-of-the-Art”. The paper was accepted for publication in Computer Vision and Image Understanding. The reviews correspond to v2 on ArXiv. The updated version will be made available on ArXiv.

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ARTICLE

A Note on Extending Tensorflow, PyTorch and Theano for Deep Learning on Custom DataStructures

Many recent deep learning frameworks such as Tensorflow, PyTorch, Theano or Torch are based on dense tensors. However, deep learning on non-tensor data structures is also interesting – especially for sparse, three-dimensional data. This article summarizes some of my experiences regarding deep learning on custom data structures in the mentioned libraries.

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ARTICLE

Examples for Getting Started with Torch for Deep Learning

This article is a collection of Torch examples meant as introduction to get started with Lua and Torch for deep learning research. The examples can also be considered individually and cover common use cases such as training on CPU and GPU, weight initialization and visualization, custom modules and criteria as well as saving and fine-tuning models.

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SERIES»Working with Ubuntu«

Building Tensorflow in an NFS-mounted $HOME, CUDA 8.0 Without Manual Driver Installation

This blog series collects useful insights for working with Ubuntu. In this article, I describe how to avoid building problems when building Tensorflow on an NFS-mounted $HOME directory and how to install CUDA 8.0 without a manual driver installation.

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ARTICLE

Inspecting Tensorflow’s Tensors using C++ and Bazel

Currently it is difficult to successfully link C++ projects with Tensorflow. However, to compile and run smaller code snippets based on Tensorflow, it might be convenient to put the code inside the tensorflow code base and compile an individual executable using Bazel.

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SERIES»Working with Ubuntu«

Installing Torch and iTorch, Installing ZeroBrane Studio with Torch Support

In this series, I blog about development and research with Ubuntu. This time: how to install LUA, Torch and iTorch and use Torch from within ZeroBrane Studio.

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ARTICLE

Installing Bazel, Masking Graphics Cards for Tensorflow

In this series, I collect problems I come across when using Ubuntu for research and development. In this article: installing Bazel on Ubuntu and masking graphics cards from being considered by Tensorflow.

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ARTICLE

Implementing Tensorflow Operations in C++ — Including Gradients

In this article, I discuss a simple Tensorflow operation implemented in C++. While the example mostly builds upon the official documentation, it includes trainable parameters and the gradient computation is implemented in C++, as well. As such, the example is slightly more complex compared to the simple ZeroOut operation discussed in the documentation.

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ARTICLE

Setting up Sphinx to Document Python Projects

Sphinx is a Python documentation tool that allows to automatically create clear documentation by parsing Python docstrings. The documentation can further be complemented using reStructuredText — a markup language similar to Markdown. This article gives a brief overview of setting up Sphinx on Ubuntu.

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ARTICLE

Implementation of Felzenszwalb and Huttenlocher’s Graph-Based Image Segmentation

This article presents an implementation of Felzenszwalb and Huttenlocher’s [1] graph-based image segmentation algorithm. The implementation is compared to the original implementation by Felzenszwalb in terms of Boundary Recall, Undersegmentation Error and Explained Variation, as used for evaluating superpixel algorithms. In addition, qualitative results are provided. The implementation is publicly available on GitHub.

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