Pytorcher's repositories
darknet
YOLOv4 / Scaled-YOLOv4 / YOLO - Neural Networks for Object Detection (Windows and Linux version of Darknet )
labelme
Image Polygonal Annotation with Python (polygon, rectangle, circle, line, point and image-level flag annotation).
Satellite-Imagery-Datasets-Containing-Ships
A list of radar and optical satellite datasets for ship detection, classification, semantic segmentation and instance segmentation tasks.
SAR-CAM
[IEEE JSTARS] Official PyTorch Implementation of "SAR Image Despeckling Using Continuous Attention Module"
github-slideshow
A robot powered training repository :robot:
SAMPLE_dataset_public
The Synthetic and Measured Paired Labeled Experiment.
NSFC-application-template-latex
国家自然科学基金申请书正文（面上项目）LaTeX 模板（非官方）
stablediffusion
High-Resolution Image Synthesis with Latent Diffusion Models
yolov5
YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite
zh-google-styleguide
Google 开源项目风格指南 (中文版)
folium
Python Data. Leaflet.js Maps.
GlobalMLBuildingFootprints
Worldwide building footprints derived from satellite imagery
ReforesTree
🌴 A dataset for estimating tropical forest biomass based on drone and field data
PlotNeuralNet
Latex code for making neural networks diagrams
DnCNN
Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising (TIP, 2017)
RIDNet
Pytorch code for "Real image denoising with feature attention", ICCV (Oral), 2019.
BGPvBGC
Prioritizing forestation based on biogeochemical and local biogeophysical impacts, Windisch et al.
gee-ccdc-tools
Tools and Earth Engine apps to interact with the outputs from the CCDC algorithm
awesome-satellite-imagery-datasets
🛰️ List of satellite image training datasets with annotations for computer vision and deep learning
nsfc
NSFC国家自然科学基金申请书正文LaTeX模板
C-C-
程序员资料免费分享，欢迎关注个人微信公众号：程序员编程指南
Latex-Template
Tmeplate for Remote Sensing Journals
resume-1
个人中文简历 Latex 源码 https://hijiangtao.github.io/
resume
An elegant \LaTeX\ résumé template. 大陆镜像 https://gods.coding.net/p/resume/git
transferlearning
Everything about Transfer Learning and Domain Adaptation--迁移学习