Pinned Repositories
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润学全球官方指定GITHUB，整理润学宗旨、纲领、理论和各类润之实例；解决为什么润，润去哪里，怎么润三大问题； 并成为新中国人的核心宗教，核心信念。
2024_Summer_AI_Camp
academicpages.github.io
Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes
AI_Logic_Resource_notes
Learn about Machine Learning and Artificial Intelligence
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, ... 🧠
AuroraNSL
Aurora prediction by neural symbolic learning
Books
My book list
https-github.com-django-sample-app
logictensornetworks
Deep Learning and Logical Reasoning from Data and Knowledge
R-GAN
Getting 3D volumetric information for an object is essential in applications ranging from autonomous manufactur- ing to robotic scene perception. In order to get 3D volumetric information for an object, RGB-D sensors are widely used to capture depth information. To reconstruct 3D volumetric infor- mation of an object, this paper designed an extended generative adversary network (GAN) with a recurrent generator. The model can take a single or a sequence of depth scans of an object to reconstruct the 3D volumetric model of the object. In precise, 3D long short-term memory (LSTM) units that are employed in the generator can extract features from the sequence of depth scans in different time steps. The reconstructed results of the proposed model are evaluated by calculating intersection over union (IoU) in both 3D space and 2D projection. The model achieved 77.71% in IoU, 80.08% in hit rate, and 97.45% in accuracy, which outperformed other methods.
FujianYan's Repositories
FujianYan/logictensornetworks
Deep Learning and Logical Reasoning from Data and Knowledge
FujianYan/R-GAN
Getting 3D volumetric information for an object is essential in applications ranging from autonomous manufactur- ing to robotic scene perception. In order to get 3D volumetric information for an object, RGB-D sensors are widely used to capture depth information. To reconstruct 3D volumetric infor- mation of an object, this paper designed an extended generative adversary network (GAN) with a recurrent generator. The model can take a single or a sequence of depth scans of an object to reconstruct the 3D volumetric model of the object. In precise, 3D long short-term memory (LSTM) units that are employed in the generator can extract features from the sequence of depth scans in different time steps. The reconstructed results of the proposed model are evaluated by calculating intersection over union (IoU) in both 3D space and 2D projection. The model achieved 77.71% in IoU, 80.08% in hit rate, and 97.45% in accuracy, which outperformed other methods.
FujianYan/-
润学全球官方指定GITHUB，整理润学宗旨、纲领、理论和各类润之实例；解决为什么润，润去哪里，怎么润三大问题； 并成为新中国人的核心宗教，核心信念。
FujianYan/2024_Summer_AI_Camp
FujianYan/academicpages.github.io
Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes
FujianYan/AI_Logic_Resource_notes
Learn about Machine Learning and Artificial Intelligence
FujianYan/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, ... 🧠
FujianYan/AuroraNSL
Aurora prediction by neural symbolic learning
FujianYan/Books
My book list
FujianYan/books-1
我读过的书。嘿嘿，分享给你。
FujianYan/cs229-2018-autumn
All notes and materials for the CS229: Machine Learning course by Stanford University
FujianYan/https-github.com-django-sample-app
FujianYan/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60个国家的400所大学用于教学。
FujianYan/Deep-Learning-Interview-Book
深度学习面试宝典（含数学、机器学习、深度学习、计算机视觉、自然语言处理和SLAM等方向）
FujianYan/Deep-Learning-Papers-Reading-Roadmap
Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech!
FujianYan/DeepLearning
深度学习入门教程, 优秀文章, Deep Learning Tutorial
FujianYan/dict-deep
An Architecture for Action Detection in Videos using Over-Complete Dictionary Learning
FujianYan/easy-rl
强化学习中文教程（蘑菇书），在线阅读地址：https://datawhalechina.github.io/easy-rl/
FujianYan/IEEE_Robotic_Club.github.io
FujianYan/interactive_projector
Fourth Year Project 2 Interactive projector implementation
FujianYan/interview
📚 C/C++面试基础知识总结
FujianYan/localization-particle-filter-python
Localize the car in a static map with a particle filter.
FujianYan/Machine-Learning
:zap:机器学习实战（Python3）：kNN、决策树、贝叶斯、逻辑回归、SVM、线性回归、树回归
FujianYan/PyNeuraLogic
PyNeuraLogic lets you use Python to create Differentiable Logic Programs
FujianYan/python_for_data_analysis_2nd_chinese_version
《利用Python进行数据分析·第2版》
FujianYan/reinforcement-learning-an-introduction
Python Implementation of Reinforcement Learning: An Introduction
FujianYan/stanford-cs-221-artificial-intelligence
VIP cheatsheets for Stanford's CS 221 Artificial Intelligence
FujianYan/Test_Projector
FujianYan/Universal_Robots_ROS_Tutorials
Tutorials around the Universal Robots ROS (1) ecosystem
FujianYan/WSU_Data_Science_Club