Hi !

Here I will share my learning experience and some useful pages or notes from other students and professors.

Pattern Recognition and Machine Learning

Pattern Recognition and Machine Learning (PRML) from Christopher Bishop

website (Some useful books here)

github (Useful code)

Keras中文文档

极市计算机视觉线上技术分享

逐句阅读100篇核心AI论文 from Bilibili

数据结构与算法(python)2020春季 from PKU 陈斌

Attention (SE block) from Bilibili

Squeeze-and-Excitation Networks

CBAM: Convolutional Block Attention Module

Machine Learning from 李宏毅 (NTU)

Hung-yi Lee’s webpage

Notes from datawhalechina

Videos from Bilibili

Surface Defect Detection (Links from CSDN and Github)

Detection方法部分汇总

yolov3

GAN

Surface-defect-Detection-dataset 合集

Unet

湖南大学一硕士论文

Learning materials from MIT

MIT OpenCourseWare

Signals-and-systems from Prof. Alan V. Oppenheim

Transfer Learning

Domain Adaptation (papers with code) from zhaoxin94 || more … from cchen-cc

CFEA: Collaborative Feature Ensembling Adaptation for Domain Adaptation in Unsupervised Optic Disc and Cup Segmentation || Code (Pytorch)