Shawn's Projects
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A guide to writing an Awesome README. Read the full article in Towards Data Science.
A collection of resources on applications of Transformers in Medical Imaging.
Pytorch implementation of Content-Noise Complementary Learning for Medical Image Denoising.
😀A toolbox for using complex valued standard network modules in PyTorch.
A high-level toolbox for using complex valued neural networks in PyTorch
A Dataset-free Self-supervised Disentangled Learning Method for Adaptive Infrared and Visible Images Super-resolution Fusion
DeepCAD: Deep self-supervised learning for calcium imaging denoising
Deep Fusion Prior for Multi-Focus Images Super Resolution Fusion.
🏫DeepLearning学习笔记以及Tensorflow、Pytorch的使用心得笔记。Dr. Sure会不定时往项目中添加他看到的最新的技术，欢迎批评指正。
👁️ 🖼️ 🔥PyTorch Toolbox for Image Quality Assessment, including LPIPS, FID, NIQE, NRQM(Ma), MUSIQ, NIMA, DBCNN, WaDIQaM, BRISQUE, PI and more...
Deep Low-Excitation Fluorescence Imaging Enhancement.
图像处理，基于Python OpenCV的图像算法研究，包括平移变换、尺度变换、旋转变换、仿射变换、灰度映射（求反、动态范围压缩、阶梯量化、阈值分割）、图像的算术运算（加法、平均法消除噪声、减法）、直方图修正（直方图均衡化、直方图规定化）、空域滤波（线性平滑滤波器、线性锐化滤波器、非线性平滑滤波器、非线性锐化滤波器）、傅里叶变换和反变换、高通和低通滤波器（分别考虑:理想滤波器、巴特沃斯滤波器，指数滤波器）、特殊高通滤波器（高频增强滤波器、高频提升滤波器）、带通带阻滤波器、同态滤波器、空域噪声滤波器、组合滤波器、无约束滤波器、有约束滤波器、变长编码、位平面编码、DPCM编码、余弦变换编码、小波变换编码、动态规划、单阈值分割、SUSAN边缘检测、主动轮廓、分水岭分割、二值形态学（腐蚀、膨胀、开启、闭合）、基于二值形态学应用(噪声消除、目标检测、区域填充)；灰度形态学（腐蚀、膨胀、开启、闭合）、基于灰度形态学的应用(形态梯度、形态平滑、高帽变换、低帽变换) 、Sobel算子、Roberts算子、拉普拉斯算子、Canny算子、Prewitt算子、高斯拉普拉斯算子
🖍️ LabelImg is a graphical image annotation tool and label object bounding boxes in images
An unofficial implement of MFF-GAN
In order to observe targets in expanded depths of view in light field imaging, we design an open source light field parallel refocusing Qt GUI software named OpenRefocus, which is based on classical spatial projection integration.
Latex code for making neural networks diagrams
PyTorch implementation of the U-Net for image semantic segmentation with high quality images
A collection of high-impact and state-of-the-art SR methods
SSD目标检测算法(Single Shot MultiBox Detector)(简单,明了,易用,全中文注释,单机多卡训练,视频检测)( If you train the model on a single computer and mutil GPU, this program will be your best choice , easier to use and easier to understand )
There are Qab/f, IQM(Image quality metric), CEN(condition entropy),SNR(Signal-to-noise ratio),Entropy(EN),OCE(Overall cross entropy) in the evalution parameters.
自动化标注工具，用来制作VOC格式的数据集
convert json/xml/bson to c++ struct
Yuanjie's academic page.
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent