R codes for data generation and visualizations are in the folder simulation.
R codes fo source data selection an visualizations are in the folder experiment_CA.
Dependencies: One can use the docker image xinranmiao/transfer_hospital_v4:v0 created by Dockerfile. Python codes are in the folder experiment_camelyon.
rastrainer rastrainer is a QGIS plugin to training remote sensing semantic segmentation model based on PaddlePaddle. UI TODO Init UI. Add Block. Add l
LoveDA: A Remote Sensing Land-Cover Dataset for Domain Adaptive Semantic Segmentation by Junjue Wang, Zhuo Zheng, Ailong Ma, Xiaoyan Lu, and Yanfei Zh
Change Detection Laboratory Developing and benchmarking deep learning-based remo
🚀 RetinaNet Horizontal Detector Based PyTorch This is a horizontal detector Ret
Universal Adversarial Examples in Remote Sensing: Methodology and Benchmark Yong
基于飞桨框架开发的高性能遥感图像处理开发套件，端到端地完成从训练到部署的全流程遥感深度学习应用。 最新动态 PaddleRS 即将发布alpha版本！欢迎大家试用 简介 PaddleRS是遥感科研院所、相关高校共同基于飞桨开发的遥感处理平台，支持遥感图像分类，目标检测，图像分割，以及变化检测等常用遥
Transfer-Learn is an open-source and well-documented library for Transfer Learning. It is based on pure PyTorch with high performance and friendly API. Our code is pythonic, and the design is consistent with torchvision. You can easily develop new algorithms, or readily apply existing algorithms.
SHOT++ Code for our TPAMI submission "Source Data-absent Unsupervised Domain Adaptation through Hypothesis Transfer and Labeling Transfer" that is ext
Transfer Style API It's an API to use with Tranfer Style App, where you can use
I have not given any examples of this in a notebook. If it seems useful / you haven't done this already, you can go ahead and build from it, otherwise no worries.
Related point for going between R and python --
Python
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h = loader_activations(loader, model, layers) # 4D array
np.save("h1.npy", h["layer_1"].numpy())
R
library("reticulate")
np <- import("numpy", convert=FALSE)
h <- py_to_r(np$load("h1.npy")) # 4D array
UDL UDL is a practicable framework used in Deep Learning (computer vision). Benchmark codes, results and models are available in UDL, please contact @
CFC-Net This project hosts the official implementation for the paper: CFC-Net: A Critical Feature Capturing Network for Arbitrary-Oriented Object Dete
IAug_CDNet Official Implementation of Adversarial Instance Augmentation for Building Change Detection in Remote Sensing Images. Overview We propose a
FactSeg: Foreground Activation Driven Small Object Semantic Segmentation in Large-Scale Remote Sensing Imagery by Ailong Ma, Junjue Wang*, Yanfei Zhon
PyTorch Remote Sensing (torchrs) (WIP) PyTorch implementation of popular datasets and models in remote sensing tasks (Change Detection, Image Super Re
Change is Everywhere Single-Temporal Supervised Object Change Detection in Remote Sensing Imagery by Zhuo Zheng, Ailong Ma, Liangpei Zhang and Yanfei
PdRSCD PdRSCD（PaddlePaddle Remote Sensing Change Detection）是一个基于飞桨PaddlePaddle的遥感变化检测的项目，pypi包名为ppcd。目前0.2版本，最新支持图像列表输入的训练和预测，如多期影像、多源影像甚至多期多源影像。可以快速完
LoveDA: A Remote Sensing Land-Cover Dataset for Domain Adaptive Semantic Segmentation by Junjue Wang, Zhuo Zheng, Ailong Ma, Xiaoyan Lu, and Yanfei Zh
SESNet for remote sensing image change detection It is the implementation of the paper: "SESNet: A Semantically Enhanced Siamese Network for Remote Se
DC-CapsNet This is a tensorflow and keras based implementation of DC-CapsNet for HSI in the Remote Sensing Letters R. Lei et al., "Hyperspectral Remot
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