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Matao's Projects

caffe icon caffe

Caffe: a fast open framework for deep learning.

cyclegan icon cyclegan

Software that can generate photos from paintings, turn horses into zebras, perform style transfer, and more.

danesfield icon danesfield

Kitware's system for 3D building reconstruction for the IARPA CORE3D program

dcgan.torch icon dcgan.torch

A torch implementation of http://arxiv.org/abs/1511.06434

extendedmorphologicalprofiles icon extendedmorphologicalprofiles

Remote sensed hyperspectral image classification with Spectral-Spatial information provided by the Extended Morphological Profiles

fucking-algorithm icon fucking-algorithm

刷算法全靠套路,认准 labuladong 就够了!English version supported! Crack LeetCode, not only how, but also why.

igan icon igan

Interactive Image Generation via Generative Adversarial Networks

lghd icon lghd

Source code of LGHD: A feature descriptor for matching across non-linear intensity variations

lidarimagehighlight icon lidarimagehighlight

Select a region in an RGB image associated with a LiDAR scan and highlight the corresponding region of the mesh

lmr icon lmr

Matlab Code for LMR: Learning for mismatch removal

local-texture-descriptors icon local-texture-descriptors

Matlab implementation, comparision and improvement of Local texture descriptors. This repo demonstrate usage of Local binary pattern (LBP), Local derivative pattern (LDP), Local Tetra pattern (LTrP), Noise Resistant LBP (NR-LBP), Histogram Refinement of Local texture descriptor for Content based image retrieval (CBIR) application.

loggabor icon loggabor

A python implementation for a LogGabor filtering and pyramid representation

lwmv3d icon lwmv3d

Light-Weight Multi-View 3D Object Detection using LIDAR and RGB

mfd icon mfd

Source code of (MFD) Multispectral Feature Descriptor.

mgans icon mgans

Precomputed Real-Time Texture Synthesis with Markovian Generative Adversarial Networks

multispectral-image-registeration icon multispectral-image-registeration

This repo contains MATLAB code for two stage multimodal (multispectral) registration. Stage I registration is based on pinhole camera model, relative orientation of two cameras or epipolar geometry. 2nd stage registration uses multimodel matching metrics (MMI & NCCR) to estimate the misregistration effect which is further used to estimate a least squared transform to remove misregistration.

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