MPI-based code for distributed HPC simulations with the sparse grid combination technique
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Updated
May 23, 2024 - C++
MPI-based code for distributed HPC simulations with the sparse grid combination technique
Periodic Mesh Generation of BCC Lattice Materials using SALOME for FEM Analysis
BCC unit cell with structured mesh in ABAQUS
[TVCG'2023] AOT-GAN for High-Resolution Image Inpainting (codebase for image inpainting)
[ECCV 2020 Spotlight] A Simple and Versatile Framework for Image-to-Image Translation
Multi-scale modeling for conservation and connectivity of African savanna elephant in Tanzania
Multi-scale model of Metabolism In Cellular Systems
Open Scripts and pipelines from the Multimodal Imaging and Connectome Analysis Lab at the Montreal Neurological Institute
Project page of the paper "Learning Multi-Scale Photo Exposure Correction" (CVPR 2021).
A slim and fast reimplementation of RACCOON iterative clustering library
This is an example to find multiple objects in images that match a template using ORB and SIFT feature detection methods. Handles different scales and rotations.
The source code for Multi-Scale Kronecker-Product Relation Networks for Few-Shot Learning
PyTorch implementation of "Avatar-Net: Multi-scale Zero-shot Style Transfer by Feature Decoration"
Graded Multiscale Fluid Topology Optimization using Neural Networks
Edge detection includes a variety of mathematical methods that aim at identifying edges, curves in a digital image at which the image brightness changes sharply or, more formally, has discontinuities. This program explores various methods to approach edge detection
Paper: Multi-Scale Ensemble Booster for Improving Existing TSD Classifiers. We proposed a highly easy-to-use performance enhancement framework called multi-scale ensemble booster(MEB), helping existing time series classification methods achieve performance leap. Our proposed MEB-ResNet achieved the most advanced time series classification ability.
Multi-scale network for image deblurring
PyTorch implementation of "Reconstruction by inpainting for visual anomaly detection (RIAD)"
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