From 3b9429c09480ec89aa17cea64f6e68444de363ac Mon Sep 17 00:00:00 2001 From: "robin.cole@earthdaily.com" Date: Fri, 21 Jun 2024 05:54:14 +0100 Subject: [PATCH] update --- README.md | 16 ++++++++++++++-- 1 file changed, 14 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index 7dcce421..dd5b9a0f 100644 --- a/README.md +++ b/README.md @@ -571,6 +571,8 @@ Note that deforestation detection may be treated as a segmentation task or a cha - [methane-emission-project](https://github.com/stlbnmaria/methane-emission-project) -> Classification CNNs was combined in an ensemble approach with traditional methods on tabular data +- [CH4Net](https://github.com/annavaughan/CH4Net) -> A fast, simple model for detection of methane plumes using sentinel-2 + - [EddyNet](https://github.com/redouanelg/EddyNet) -> A Deep Neural Network For Pixel-Wise Classification of Oceanic Eddies - [schisto-vegetation](https://github.com/deleo-lab/schisto-vegetation) -> Deep Learning Segmentation of Satellite Imagery Identifies Aquatic Vegetation Associated with Snail Intermediate Hosts of Schistosomiasis in Senegal, Africa @@ -924,6 +926,10 @@ Extracting roads is challenging due to the occlusions caused by other objects an - [contrastive_SSL_ship_detection](https://github.com/alina2204/contrastive_SSL_ship_detection) -> Contrastive self supervised learning for ship detection in Sentinel 2 images +- [airbus-ship-detection](https://github.com/odessitua/airbus-ship-detection) -> using DeepLabV3+ + +- [Unet with web-application applied to Airbus ships](https://github.com/glibesyck/ImageSegmentation) + ### Segmentation - Other manmade - [Aarsh2001/ML_Challenge_NRSC](https://github.com/Aarsh2001/ML_Challenge_NRSC) -> Electrical Substation detection @@ -1378,7 +1384,7 @@ Detecting the most noticeable or important object in a scene - [Arbitrary-Oriented Ship Detection through Center-Head Point Extraction](https://github.com/JinleiMa/ASD) -- [ship_detection](https://github.com/rugg2/ship_detection) -> using an interesting combination of CNN classifier, Class Activation Mapping (CAM) & UNET segmentation. Accompanying [three part blog post](https://www.vortexa.com/insights/technology/satellite-images-object-detection/) +- [ship_detection](https://github.com/rugg2/ship_detection) -> using an interesting combination of CNN classifier, Class Activation Mapping (CAM) & UNET segmentation - [Building a complete Ship detection algorithm using YOLOv3 and Planet satellite images](https://medium.com/intel-software-innovators/ship-detection-in-satellite-images-from-scratch-849ccfcc3072) -> covers finding and annotating data (using LabelMe), preprocessing large images into chips, and training Yolov3. [Repo](https://github.com/amanbasu/ship-detection) @@ -1698,6 +1704,8 @@ Regression in remote sensing involves predicting continuous variables such as wi - [GEDI-BDL](https://github.com/langnico/GEDI-BDL) -> Global canopy height regression and uncertainty estimation from GEDI LIDAR waveforms with deep ensembles +- [Global-Canopy-Height-Map](https://github.com/AI4Forest/Global-Canopy-Height-Map) -> Estimating Canopy Height at Scale (ICML2024) + - [HighResCanopyHeight](https://github.com/facebookresearch/HighResCanopyHeight) -> code for Meta paper: Very high resolution canopy height maps from RGB imagery using self-supervised vision transformer and convolutional decoder trained on Aerial Lidar - [Traffic density estimation as a regression problem instead of object detection](https://omdena.com/blog/ai-road-safety/) -> inspired by paper: Traffic density estimation method from small satellite imagery: Towards frequent remote sensing of car traffic @@ -2219,7 +2227,7 @@ The analysis of time series observations in remote sensing data has numerous app - [Rapid Wildfire Hotspot Detection Using Self-Supervised Learning on Temporal Remote Sensing Data](https://github.com/links-ads/igarss-multi-temporal-hotspot-detection) -- [stenn-pytorch](https://github.com/ThinkPak/STENN) -> A Spatio-temporal Encoding Neural Network for Semantic Segmentation of Satellite Image Time Series +- [stenn-pytorch](https://github.com/ThinkPak/stenn-pytorch) -> A Spatio-temporal Encoding Neural Network for Semantic Segmentation of Satellite Image Time Series # ## Crop classification @@ -2423,6 +2431,8 @@ Remote sensing images are used in disaster response to identify and assess damag - [skai](https://github.com/google-research/skai) -> a machine learning based tool from Goolge for performing automatic building damage assessments on aerial imagery of disaster sites. +- [building-damage-assessment-cnn-siamese](https://github.com/microsoft/building-damage-assessment-cnn-siamese) -> from the Microsoft Ai for Good lab + # ## Super-resolution @@ -3733,6 +3743,8 @@ Training data can be hard to acquire, particularly for rare events such as chang - [LHRS-Bot](https://github.com/NJU-LHRS/LHRS-Bot) -> Empowering Remote Sensing with VGI-Enhanced Large Multimodal Language Model +- [Awesome-VLGFM](https://github.com/zytx121/Awesome-VLGFM) -> Towards Vision-Language Geo-Foundation Models: A Survey + # ## Foundational models