sigma (wzwcqu)

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STB-VMM

STB-VMM: Swin Transformer Based Video Motion Magnification (official repository)

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motion_magnification_learning-based

An unofficial implementation of "Learning-based Video Motion Magnification" in Pytorch.

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Kanade-Lucas-Tomasi-KLT-feature-tracker

Kanade-Lucas-Tomasi (KLT) tracking algorithm and Harris Corner Detection implementation

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d2l-zh

《动手学深度学习》:面向中文读者、能运行、可讨论。中英文版被70多个国家的500多所大学用于教学。

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Geospatial-COSICorr3D

Tools and libraries for processing satellite images (push-broom, frame and push-frame), including rigorous sensor model (RSM) refinement, rational function model (RFM) refinement, orthorectification, sub-pixel image correlation, and 3D surface displacement extraction.

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crack_detection_CNN_masonry

This GitHub Repository was produced to share material relevant to the Journal paper "Automatic crack classification and segmentation on masonry surfaces using convolutional neural networks and transfer learning" by D. Dais, İ. E. Bal, E. Smyrou, and V. Sarhosis published in "Automation in Construction".

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Industrial-Machinery-Anomaly-Detection

Extract features and detect anomalies in industrial machinery vibration data using a biLSTM autoencoder

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pbMoMa

Phase based video motion magnification

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3d-shm

This repository contains the codes for 3D contactless vibration monitoring of shake-table tests using RGB-D cameras

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Non-contact-measurement-of-Pulse-Rate

A Computer Vision project that helps in the real time non-contact measurement of pulse rate using Eulerian Video Magnification.

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Measurement-of-key-parameters-of-wing-vibration-modulus

The project goal is to use binocular vision and non-contact measurement methods to identify modal parameters of large antennas, solar wings, etc. in orbit.

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ML_civil_engineering

Machine Learning in Civil Engineering

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repincv

This repository contains the source code of master's thesis titled "Investigating the Impact of Randomness in Reproducibility in Computer Vision: A Study on Applications in Civil Engineering and Medicine "

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Visual-Mic

When sound hits an object, it causes small vibrations on the object’s surface. Here we show how, using only high-speed video of the object, we can extract those minute vibrations and partially recover the sound that produced them, allowing us to turn everyday objects—a glass of water, a potted plant, a box of tissues, or a bag of chips—into visual microphones.

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Video_Analytics

Developing sensor using Computer Vision to monitor movement and produce vibration trace of critical bridge elements.

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LISRD

Local Invariance Selection at Runtime for Descriptors (LISRD)

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StrainNet

Subpixel displacement and strain fields estimation with deep learning

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ORB-based-displacement-monitoring-system

A displacement monitoring system using opencv-python based on ORB.

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IPMC-Displacement-Vision-System

A computer vision system to measure the displacement and bending angle of ionic polymer-metal composite (IPMC)

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Framing_Displacements

Repository for storing code related to identifying framing displacements between pairs of images.

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Deep-Dic-deep-learning-based-digital-image-correlation

Deep DIC: Deep Learning-Based Digital Image Correlation for End-to-End Displacement and Strain Measurement

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pyidi

Python Image Displacement Identification

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visual-odometry

Implementation of monocular and stereo visual odometry. Tracks vehicle displacement from origin using successive video frames.

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video_tracking

This Python Notebook allows you to perform a video tracking of an object and obtain its kinematic information such as displacement, speed and acceleration.

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video_object_tracking

Calculates the displacement of an object in a video using optical flow methods

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Python-VO

A simple python implemented frame-by-frame visual odometry with SuperPoint feature detector and SuperGlue feature matcher.

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cnn-matching

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

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annotated_deep_learning_paper_implementations

🧑‍🏫 60 Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠

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mala_public

supporting simulation code for the paper "Log-concave sampling: Metropolis-Hastings algorithms are fast!"

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