dmwu1115 Goto Github PK

followers: 0.0 following: 0.0 repos: 57.0 gists: 0.0

Type: User

dmwu1115's Projects

.tmux

🇫🇷 Oh my tmux! My self-contained, pretty & versatile tmux configuration made with ❤️

autoencoder-ssim-for-unsupervised-anomaly-detection-

Improving Unsupervised Defect Segmentation by Applying Structural Similarity to Autoencoders

automatic-sem-image-segmentation

Workflow for Simulation and Automatic Semantic Segmentation of Electron Microscopy Images

awesome-edge-detection-papers

:books: A collection of edge/contour/boundary detection papers and toolbox.

cnn-matching

Source code and datadset for "Deep learning algorithm for feature matching of cross modality remote sensing images"

cnn-registration

An image registration method using convolutional neural network features.

computer-vision-in-action

学习闭环《计算机视觉实战演练：算法与应用》中文电子书、源码、读者交流社区（持续更新中 ...） 📘 在线电子书 https://charmve.github.io/computer-vision-in-action/ 👇项目主页

contour-guided-registration

Sequential rigid registration and measurement in serial imaging for each contour of an RT Structure set (Elastix, Plastimatch, ffmpeg)

cpd

C++ implementation of the Coherent Point Drift point set registration algorithm.

cpp-primer-plus-6th

《C++ Primer Plus 第6版（中文版）》原书代码、习题答案和个人笔记，仅供学习和交流。

cv

✔️最全面的深度学习CV 笔记【吴恩达深度学习】【李沐动手学深度学习】【我是土堆 Pytorch】

d2-net

D2-Net: A Trainable CNN for Joint Description and Detection of Local Features

feature-matching-and-position-matching-between-optical-and-sar

Using Deep learning to locate the Synthetic Aperture Radar(SAR) images to the counterpart of Optical images.

hands-on-ml-2e-zh

:book: [译] Sklearn 与 TensorFlow 机器学习实用指南第二版

handson-ml

⛔️ DEPRECATED – See https://github.com/ageron/handson-ml3 instead.

handson-ml3

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.

human-detection-using-hog-lbp-neural-networks

The program uses HOG and LBP features to detect human in images. First, use the HOG feature only to detect humans. Next, combine the HOG feature with the LBP feature to form an augmented feature (HOG-LBP) to detect human. A Two-Layer Perceptron (feedforward neural network) will be used to classify the input feature vector into human or no-human.

hurlex-doc

hurlex 小内核分章节代码和文档

icp

A Python implementation of the Iterative Closest Point algorithm

image-feature-detection-using-phase-stretch-transform

PST or Phase Stretch Transform is an operator that finds features in an image. PST implemented using MATLAB here, takes an intensity image I as its input, and returns a binary image out of the same size as I, with 1's where the function finds sharp transitions in I and 0's elsewhere.

dmwu1115 Goto Github PK

dmwu1115's Projects

Recommend Projects

Recommend Topics

Recommend Org