An unofficial implementation of the Pure Dilated Residual U-Net architecture.
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Updated
Jun 22, 2024 - Python
An unofficial implementation of the Pure Dilated Residual U-Net architecture.
Simple implementation of UNet architecture in PyTorch
Original Pytorch Implementation of FLAME: Facial Landmark Heatmap Activated Multimodal Gaze Estimation
PyTorch implementation of the Dense Inception U-Net
"Very Deep Convolutional Networks for Large-Scale Image Recognition" by Karen Simonyan and Andrew Zisserman.
"Going Deeper with Convolutions" by Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke and Andrew Rabinovich.
"SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB model size" by Forrest N. Iandola, Song Han, Matthew W. Moskewicz, Khalid Ashraf, William J. Dally and Kurt Keutzer.
"U-Net: Convolutional Networks for Biomedical Image Segmentation" by Olaf Ronneberger, Philipp Fischer and Thomas Brox
"Deep Residual Learning for Image Recognition" by Kaiming He, Xiangyu Zhang, Shaoqing Ren and Jian Sun
"Densely Connected Convolutional Networks" by Gao Huang, Zhuang Liu, Laurens van der Maaten and Kilian Q. Weinberger.
Code for the paper "Thermodynamics-informed graph neural networks" published in IEEE Transactions on Artificial Intelligence (TAI).
[ICLR2024] Official repo for paper "PnP Inversion: Boosting Diffusion-based Editing with 3 Lines of Code"
"ImageNet Classification with Deep Convolutional Neural Networks" by Alex Krizhevsky, Ilya Sutskever and Geoffrey Hinton.
"Gradient Based Learning Applied to Document Recognition" by Yann LeCun, Léon Bottou, Yoshua Bengio and Patrick Haffner.
Official implementation of Bagging Folds using Synthetic Majority Oversampling for Imbalance Classification
re-implementaion of "A watermark for Large Language Models" ( https://arxiv.org/abs/2301.10226 )
🚀 A repository that collects code that implements models in various fields. 🚀
PRS: Sharp Feature Priors for Resolution-Free Surface Remeshing
Implementation of the Image Reflection Suppression algorithm by Yang et. al in Python.
Code for the paper "Deep learning of thermodynamics-aware reduced-order models from data" published in Computer Methods in Applied Mechanics and Engineering (CMAME).
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