With the help of CLion documentation, I was able to find the base class for layers in OpenCV dnn. Here you go, check line 174. Have no idea why this class definition lies so deep.

This class has the following members and member functions, and we’ll… Read more...

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This blog aims to briefly present a roadmap to understand the source code of OpenCV’s `dnn` module.

Example usage

Before diving deep in to the code, you can find an example usage of this module here. This example shows how to load a pretrained… Read more...

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This post 1) summarizes the paper “unsuperverized representation learning with deep convolutional generative adversarial networks (DCGAN)” as well as my empirical experiment results.

Key idea 

This paper teaches a family… Read more...

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This post annotate PyTorch’s implementation of ResNet.

ResNet is one of the most widely used network structure for image tasks in the industry.

The motivation for the original idea is deep neural networks, if we simply stack layers … Read more...

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This post briefly documents variations of optimization algorithms and best practices. It’s a summary of this source . Also this course note is helpful for a review.

Tricks in checking if a gradient is implemented correctly: use centered… Read more...

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It took me a long while (~ 4 days?) to understand the theories of Variation autoencoder (VAE) and how to actually implement it. And it’s not entirely my fault, because:

  • The original paper (Auto-Encoding Variational Bayes) explains
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Introduction

I spent the last week of 2018 and the first week of 2019 preparing CityGML data for a machine learning project. In particular, I need to extract 3D point cloud representation of individual buildings in New York (and Berlin and Zurich)… Read more...

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This post describes how to implement stochastic gradient in a distributed fashion with MPI. It will cover the following topics in a high-level fashion, as it is challenging to cover every details in a single post. I will point to other resources… Read more...

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This post describes how to write CUDA C code to perform 2D convolution on GPU with tiling technique. It is very brief, only covers basic concepts but with links to code examples. We are not going to use cuDNN, only the bare bones of CUDA. But hereRead more...

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This post follows this post last year about vanilla Recurrent Neural Network structures.

One of the ultimate goal of a recurrent neural network is to summarize a sequence of vectors into a single vector representing all the information.

In… Read more...

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