LeeBDa lbd-hfut
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Shanghai Jiaotong University
- Shanghai, China
- https://orcid.org/0009-0009-7596-6786
Stars
Camera parameters are encoded into neural network weights, and differentiable triangulation and reprojection errors are used as physical constraints to learn camera intrinsic parameters, extrinsic ...
An implementation of Mesh-based Digital Image Correlation (Mesh-DIC/FE-DIC) for full-field displacement and strain measurement.
A method for solving digital image correlation based on physical information network
An implementation of Subset-based Digital Image Correlation (Subset-DIC) for full-field displacement and strain measurement.
High-efficiency PINN-based Digital Image Correlation framework with multi-segment partitioning for scalable full-field deformation measurement.
This is a PyTorch implementation of the ECCV2020 paper "DeepSFM: Structure From Motion Via Deep Bundle Adjustment".
PaddleScience is SDK and library for developing AI-driven scientific computing applications based on PaddlePaddle.
Framework providing pythonic APIs, algorithms and utilities to be used with PhysicsNeMo core to physics inform model training as well as higher level abstraction for domain experts
Windowed Fourier ridge algorithm based on Vulkan implementation
Solve forward and inverse problems related to partial differential equations using finite basis physics-informed neural networks (FBPINNs)
Implementation of Physics-Informed Diffusion Models (ICLR 2025)
Physics-informed convolutional-recurrent neural networks for solving spatiotemporal PDEs
Physics-informed convolutional-recurrent neural networks for solving spatiotemporal PDEs
shang1117 / pinn_hole
Forked from sebatomon/numerical_examplesApplication of different algorithms and tools to solve the elastic problem on a plate with a hole.
📚 Modern C++ Tutorial: C++11 to C++26 On the Fly | https://changkun.de/modern-cpp/
The application and comparison of deep learning methods and the subset least squares method in DIC (Digital Image Correlation) strain computation.
All course materials for the Zero to Mastery Deep Learning with TensorFlow course.
Materials for the Learn PyTorch for Deep Learning: Zero to Mastery course.
Pytorch implementation of Diffusion Models (https://arxiv.org/pdf/2006.11239.pdf)
搞定C++:punch:。C++ Primer 中文版第5版学习仓库,包括笔记和课后练习答案。
Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains