Pytorch code for ICCV'23 paper. NEO 360: Neural Fields for Sparse View Synthesis of Outdoor Scenes
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Updated
Jul 5, 2024 - Python
Pytorch code for ICCV'23 paper. NEO 360: Neural Fields for Sparse View Synthesis of Outdoor Scenes
These are Coursera assignment of Course Deep Learning Specialization, this one is course 4
Modified Residual U-Net (ResUnet) for Image Segmentation
Up-sampling and denoising signals using a deep neural network model
Using a modified ResNet to enhance image classification on the Cifar-10 dataset
The code repository for "Parkinson’s severity diagnosis explainable model based on 3D multi-head attention residual network"
Deep learning model to predict the normal flow between two consecutive frames, being the normal flow the projection of the optical flow on the gradient directions.
Final project assigned for the Introduction to Image Processing (EE 475) course in the Spring 2023 semester.
PyTorch implementation of ResUNet++ for Medical Image segmentation
Official code for ResUNetplusplus for medical image segmentation (TensorFlow & Pytorch implementation)
Official implementation of NanoNet: Real-time medical Image segmentation architecture (IEEE CBMS)
A PyTorch implementation of Google Research's Noisy Student Training. Applied on training a series of ResNets on Food101 image classification dataset
Robust learning with implicit residual networks
A dynamically adaptable neural network-based replay spoofing attack detection system.
Code for doing Argument Structure Prediction using Residual Networks and (almost) without symbolic features
PyTorch implementations of the deep residual networks published in "Deep Residual Learning for Image Recognition" by Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun
Codebase accompanying the paper 'Widening the Representation Bottleneck in Neural Machine Translation with Lexical Shortcuts', (Emelin, Denis, Ivan Titov, and Rico Sennrich, Fourth Conference on Machine Translation, Florence, 2019.)
Solving board games like Connect4 using Deep Reinforcement Learning
Tensorflow implementation of Learning Residual Images for Face Attribute Manipulation
Meta-Zeta是一个基于强化学习的五子棋(Gobang)模型,主要用以了解AlphaGo Zero的运行原理的Demo,即神经网络是如何指导MCTS做出决策的,以及如何自我对弈学习。源码+教程
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