Tag Archives: OpenCV

Recurrent Neural Networks I

RNNs Recurrent neural networks are very famous recently, they play as important roles as convolutional neural networks. RNNs can use their internal memory to process arbitrary sequences of inputs, so not only images, they work well on speech recognition and natural language processing tasks. There are several type of RNNs, as the beginning, we focus our attention on […]

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Denoising Autoencoder

I chose “Dropped out auto-encoder” as my final project topic in the last semester deep learning course, it was simply dropping out units in regular sparse auto-encoder, and furthermore, in stacked sparse auto-encoder, both in visible layer and hidden layer. It does not work well on auto-encoders, except can be used in fine-tune process of stacked sparse […]

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Convolutional Neural Networks II

Since the last CNN post, I was working on a new version of CNN, which support multi-layers Conv and Pooling process, I’d like to share some experience here. VECTOR VS HASH TABLE You can see in the last post, I used vector of Mat in convolution steps, it works well when we only have one […]

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Convolutional Neural Networks

WHAT IS CNN A Convolutional Neural Network (CNN) is comprised of one or more convolutional layers, pooling layers and then followed by one or more fully connected layers as in a standard neural network. The architecture of a CNN is designed to take advantage of the 2D structure of an input image (or other 2D input […]

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A Simple Deep Network

During this spring break, I worked on building a simple deep network, which has two parts, sparse autoencoder and softmax regression. The method is exactly the same as the “Building Deep Networks for Classification” part in UFLDL tutorial. For better understanding it, I re-implemented it using C++ and OpenCV.  GENERAL OUTLINE Read dataset (including training data […]

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Poisson Blending II

I re-wrote the Poisson Blending code using C++ and OpenCV. About the Algorithm, see my Previous Poisson Blending post. This time, I just used the most stupid way, just solving the Poisson Equation. You can improve it by using advanced methods. About solving discrete Poisson Equation using Jacobi, SOR, Conjugate Gradients, and FFT, read THIS.   In […]

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Softmax Regression (with OpenCV)

This is the same algorithm with the previous SOFTMAX REGRESSION post. Because I’m going to try to build deeper neural networks for images, so as a review of OpenCV programming, I rewrote the Softmax regression code using OpenCV mat, instead of Armadillo. I used Matlab, Octave, Armadillo a lot these days, it is kind of […]

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C++ code for reading MNIST dataset

Here’s a code for reading MNIST dataset in C++, the dataset can be found HERE, and the file format is as well. Using this code, you can read MNIST dataset into a double vector, or an OpenCV Mat, or Armadillo mat. Feel free to use it for any purpose. (part of this code is stolen from […]

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A Simple QR Code Scanner [part 1]

QR Code is kind of matrix barcode, it is recently very popular because of its fast read speed and big storage capacity, we can see it everywhere, Jeky even wanted to tattoo one on his body. A QR code makes up by  black square dots and white square grid, black dots arrange in white background, […]

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SURF

SURF (Speeded Up Robust Features), is a feature detector, we talked about SIFT before, and SURF is sort of derivative of SIFT. SURF is based on sums of 2D Haar wavelet responses and makes an efficient use of integral images. I’ll not represent the whole story of SURF, because its idea is very similar to SIFT, so […]

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