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2022-machine-learning-specialization

automatic_landslides_identification_with_insar

Automatic identification of active landslides over wide areas from multi-source InSAR measurements using Faster RCNN

awesome-vision-attentions

Summary of related papers on visual attention. Related code will be released based on Jittor gradually.

deepnetsforeo

Deep networks for Earth Observation

external-attention-pytorch

🍀 Pytorch implementation of various Attention Mechanisms, MLP, Re-parameter, Convolution, which is helpful to further understand papers.⭐⭐⭐

insar-time-series-clustering

First version of the code linked to the October submission to Internal Journal of Applied Earth Observation and Geoinformation

lag-llama

Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting

landslide-detection

遥感图像滑坡识别

landslide-susceptibility-prediction-using-machine-learning-algorithms

Landslide Susceptibility Prediction and Identification of Most Significant Factors that best describe an area is susceptible to Landslides or not based on Explainable Artificial Intelligence to solve the challenging BlackBox problem of state art Artificial Intelligence based methods.

landslide_detection_faster-rcnn

利用faster-rcnn目标检测网络实现滑坡的提取

lsat

Landslide Susceptibility Assessment Tools - Project Manager Suite

pca-kmeans-tft-time-series-clustering-and-prediction

This repository contains code and sample data related to the title "InSAR time series clustering and Landslide display prediction with multiple variables and time series: A case study of the Badui area in Eastern Tibet", mainly focusing on clustering and prediction of time series.

pyecharts

🎨 Python Echarts Plotting Library

pyts

A Python package for time series classification

r-arcgis-lsm_toolpack

This tool is to develop an easy-to-use tool package called Landslide Susceptibility Mapping Tool Pack (LSM Tool Pack) for producing landslide susceptibility maps based on integrating R with ArcMap Software. The proposed tool contains 5 main modules namely: (1) Data Preparation (DP), (2) Feature (Factor) Selection (FS), (3) Logistic Regression (LR),

sar-landslide-detection-pretraining

Repository for the paper "SAR-based landslide classification pretraining leads to better segmentation"

time-series-forcasting

In this repository i have implemented various Deep Learning multivariate and multiheaded time series forecasting models . Apart from that i have also uploaded the Ipython file of Grid_Search and Ensemble_Learning technique which i have implemented during my summer intern of IIT-Mandi(May 2019)

unetforlandslide

刘老师团队选拔：深度学习Pytorch框架构建Unet模型识别滑坡

x-anylabeling

Effortless data labeling with AI support from Segment Anything and other awesome models.