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Satellite Image Classification using semantic segmentation methods in deep learning
Urban change model designed to identify changes across 2 timestamps
The pytorch implemention of FCCDN for change detection task
Flops counter for convolutional networks in pytorch framework
TensorFlow implementation of focal loss
Binary and Categorical Focal loss implementation in Keras.
全中文注释.(The loss function of retinanet based on pytorch).(You can use it on one-stage detection task or classifical task, to solve data imbalance influence).用于one-stage目标检测算法,提升检测效果.你也可以在分类任务中使用该损失函数,解决数据不平衡问题.
Focal Loss for multi-class classification
FPGA: Fast Patch-Free Global Learning Framework for Fully End-to-End Hyperspectral Image Classification (TGRS 2020) https://ieeexplore.ieee.org/document/9007624
Source code and models GALD net (BMVC-2019)and Dual-Seg Net (BMVC-2019)
wgan, wgan2(improved, gp), infogan, and dcgan implementation in lasagne, keras, pytorch
Code for paper: Group-CAM: Group Score-Weighted Visual Explanations for Deep Convolutional Networks
This repository contains the software developed for the project of Heterogeneous Change Detection in Remote Sensing Images.
PyTorch实现高分遥感语义分割(地物分类)
Pytorch and Keras Implementations of Hyperspectral Image Classification -- Traditional to Deep Models: A Survey for Future Prospects.
Official PyTorch implementation of CVPR'22 paper: HyperTransformer: A Textural and Spectral Feature Fusion Transformer for Pansharpening
Official Pytorch Implementation of Adversarial Instance Augmentation for Building Change Detection in Remote Sensing Images.
ICNet implemented by pytorch, for real-time semantic segmentation on high-resolution images, mIOU=71.0 on cityscapes, single inference time is 19ms, FPS is 52.6.
some loss functions of image segmentation
Pytorch implementation of U-Net, R2U-Net, Attention U-Net, and Attention R2U-Net.
Attention mechanism Implementation for Keras.
An implementation of Grad-CAM with keras
Implementation of Squeeze and Excitation Networks in Keras
Keras library for building (Universal) Transformers, facilitating BERT and GPT models
The Tensorflow, Keras implementation of U-net, V-net, U-net++, R2U-net, Attention U-net, ResUnet-a, U^2-Net, and UNET 3+ with optional ImageNet-trained backbones.
Master thesis about change detection in satellite imagery using Deep Learning
Get Landsat surface reflectance time-series from google earth engine
A mmseg-style demo code of Lawin(large window) Transformer https://arxiv.org/abs/2201.01615. The complete project will be available soon.
Lightweight models for real-time semantic segmentation(include mobilenetv1-v3, shufflenetv1-v2, igcv3, efficientnet).
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.