daili0015 / SEU_Net_ConnectLinks
SEU网络自动重连
☆13Updated 6 years ago
Alternatives and similar repositories for SEU_Net_Connect
Users that are interested in SEU_Net_Connect are comparing it to the libraries listed below
Sorting:
- 算法、编程学习笔记☆48Updated 3 years ago
- Visualization CNN model by Keras.☆73Updated 6 years ago
- 天池比赛,kaggle等等(Keras/PyTorch实战)☆182Updated 5 years ago
- CV 方向论文阅读以及手写代码实现☆112Updated 3 years ago
- personal practice(个人练习,实现了深度学习中的一些算法,包括:四种初始化方法(zero initialize, random initialize, xavier initialize, he initialize),深度神经网络,正则化,dropout,…☆224Updated 6 years ago
- ☆80Updated 6 years ago
- rscup2019,分类赛道☆32Updated 6 years ago
- kaggle competition: Dogs_vs_Cats_PyTorch Presentation(Getting started with PyTorch)☆67Updated 4 months ago
- 第五届百度西安交大大数据竞赛 城市区域功能分类 Baseline☆94Updated 3 years ago
- my solution with 0.67 accuracy☆79Updated 6 years ago
- This is a library of machine learning. I designed it to learn more about machine learning.☆51Updated 5 years ago
- 天池2019 年县域农业大脑AI挑战赛 第11名解决方案 deeplabv3-pytorch, crf等☆25Updated 6 years ago
- ☆185Updated 6 years ago
- notes and exercises☆31Updated 7 years ago
- 机器学习实战☆152Updated 2 years ago
- ML/DL学习笔记(基础+论文)☆282Updated 5 years ago
- ☆16Updated 6 years ago
- In this repository, I will implement some machine learning algorithms in Python, and show how to use it in a notebook. I feel it interest…☆42Updated 6 years ago
- SPP net详解☆70Updated 5 years ago
- Baidu Big Data Contest 2019: Urban Region Function Classification, top4☆28Updated 6 years ago
- 一个面向初学者的,友好的Keras入门教程☆123Updated 6 years ago
- ☆121Updated 5 years ago
- Spatial and channel-wise attention☆38Updated 7 years ago
- DenseNet with Deep Residual Channel-Attention Blocks for Single Image Super Resolution☆32Updated 6 years ago
- pytorch learning tutorials☆121Updated 3 years ago
- A Strong Baseline with Many Tricks for Image Classification☆47Updated 2 years ago
- 小作业 使用遗传算法和OTSU做图像分割☆36Updated 7 years ago
- 深度学习常用优化方法详解☆269Updated 8 years ago
- practice on CIFAR10 with Keras☆43Updated 7 years ago
- 深度学习500问,以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述,以帮助自己及有需要的读者。 全书分为18个章节,近30万字。由于水平有限,书中不妥之处恳请广大读者批评指正。 未完待续............ 如有意合作,联系sc…☆10Updated 6 years ago