Kun SUN's Projects
simultaneous extraction of building height and footprint
Official implement of Paper:A deeply supervised image fusion network for change detection in high resolution bi-temporal remote sening images
Street & Building segmentation from online map images
This repo includes ChatGPT prompt curation to use ChatGPT better.
🛰️ List of satellite image training datasets with annotations for computer vision and deep learning
:metal: awesome-semantic-segmentation
Boundary Enhancement Semantic Segmentation for Building Extraction from Remote Sensed Image
semantic segmentation,DeepLab,U-Net,SCSENet,BAM,DenseASPP,Remote sensing,tensorflow2
Training dataset for supervised learning
Building Extraction / Semantic Segmentation from remote sensing images
Practical Project for Semantic Segmentation of Building Footprint from Satellite Images
Building footprint segmentation from satellite and aerial imagery
Building segmentation in cooperation with the KartAi research project. This repository will explore BEiT and a multi-scale model to be used for building segmentation from orthophotos.
building segmentation dataset
A repository for the BUilding MAterials model as described in the Journal of Cleaner Production
A Global Database on Whole Life Carbon, Energy and Material Intensity of Buildings (CarbEnMats-Buildings)
**行政区划矢量图,ESRI Shapefile格式,共四级:国家、省/直辖市、市、区/县。关键字:**行政区划图;**地图;**行政区;**行政区地图;行政区地图;行政区;行政区划;地图;矢量数据;矢量地理数据;省级;直辖市;市级;区/县级;行政区划图。
Python (3.8+) version of CLIMADA
Bounding Boxes Are All We Need: Street View Image Classification via Context Encoding of Detected Buildings
This is my project to count number of floors from building front image
We present a novel complex-valued convolutional and multi-feature fusion network (CVCMFF Net) specifically for building semantic segmentation of InSAR images. It can effectively segment the layover, shadow, and background on both the simulated InSAR building images and the real airborne InSAR images. The segmentation performance of CVCMFF Net is significantly improved compared with other state-of-the-art networks. The comparative experiments are link to https://github.com/Jiankun-chen/building-semantic-segmentation-of-InSAR-images
A collection of open source projects relevant for industrial ecology practitioners, hosted on GitHub and beyond
深度学习以进行时间序列预测
detecting the number of floors with opencv
Fast instance selection method
Code for DrivenData Open AI Caribbean Challenge. 2nd place solution.