hulaba

2021_Nkwasa_etal_HESS

Scripts used to incorporate global phenology datasets into regional-global SWAT+ models

Artificial-Intelligence-in-Agriculture-Diseased-Leaf-Classification

AI is steadily emerging and making a significant impact in various sectors such as education, healthcare, transportation, finance, manufacturing, agriculture and many more. Agriculture Industry - the mainstay profession in numerous countries worldwide is also turning towards artificially intelligent technologies to enhance crop yield productivity while utilizing resources more sustainably, control pest infestations, monitoring soil and crop health, precision farming and predictive analytics.

awesome-neural-rendering

A collection of resources on neural rendering.

Context-Aware-Representation-Crop-Yield-Prediction

Code for ICDM 2020 paper Context-aware Deep Representation Learning for Geo-spatiotemporal Analysis

Crop-Segmentation-and-Yield-Count-using-Graph-based-approach

With the given a set of images of the Arecanuts yield, count the number of Arecanuts available in each bunch and based on the count obtained from each bunch, estimate the total number of nuts available from the yield using efficient Graph Based approach.

crop-type-mapping

Source code to Rußwurm & Körner 2019. Self-Attention for Raw Optical Satellite Time Series Classification

crop-type-mapping-1

Crop type mapping of small holder farms in Ghana, and South Sudan

Crop-Yield-Estimation-Model

Random forest regression yield estimation model with genetic algorithm-based feature selection.

Crop-Yield-Prediction-Comparison-using-ML-DL-Techniques

In this project, we compare and predict the yield of five crops (wheat, barley, jowar, rapeseed & mustard, and bajra) in Rajasthan (district-wise) using three machine learning techniques: random forest, lasso regression and SVM, and two deep learning techniques: gradient descent and RNN LSTM. To apply the models to our data, we divided it into training and testing datasets. Each model is tested twice: once with only "area" and "production" in mind, and then again with additional factors (rainfall and soil type) in mind to predict crop yield. To find the model that most accurately predicts the yield, R2 score, Root Mean Squared Error (RMSE) and Mean Average Error (MAE) are calculated for each model.

Salinas-dataset-Classification

This data set comes from Hyperspectral Remote Sensing Scenes

hulaba/BasicIRSTD

BasicIRSTD toolbox

hulaba/CogVLM

a state-of-the-art-level open visual language model | 多模态预训练模型

hulaba/DL4sSR

Benchmark for a paper submitted to Information Fusion

hulaba/DOFA

Code for Neural Plasticity-Inspired Foundation Model for Observing the Earth Crossing Modalities

hulaba/downscale-satelliteLST

A python class for enhancing the spatial resolution of satellite-derived Land Surface Temperatures (LST) using statistical downscaling.

hulaba/ftw-baselines

Code for running baseline models/experiments with the Fields of The World dataset

hulaba/Geo-SAM

A QGIS plugin tool using Segment Anything Model (SAM) to accelerate segmenting or delineating landforms in geospatial raster images.

hulaba/GLM-4

GLM-4 series: Open Multilingual Multimodal Chat LMs | 开源多语言多模态对话模型

hulaba/graphcast

hulaba/IF_CALC

The repository contains the implementations for Coupled Adversarial Learning for Fusion Classification of Hyperspectral and LiDAR Data

hulaba/imgaug

Image augmentation for machine learning experiments.

hulaba/labelImg

LabelImg is now part of the Label Studio community. The popular image annotation tool created by Tzutalin is no longer actively being developed, but you can check out Label Studio, the open source data labeling tool for images, text, hypertext, audio, video and time-series data.

hulaba/LST-downscaling-to-10m-GEE

A tool to downscale Landsat Land Surface Temperature to 10 m using Sentinel-2 data in GEE. Attachment for the article in Remote Sensing: Onačillová et al. 2021: Combining Landsat 8 and Sentinel-2 Data in Google Earth Engine to Derive Higher Resolution Land Surface Temperature Maps in Urban Environment. https://doi.org/10.3390/rs14164076

hulaba/markitdown

Python tool for converting files and office documents to Markdown.

hulaba/meteor

hulaba/MSI-Net

hulaba/OverlapPredator

[CVPR 2021, Oral] PREDATOR: Registration of 3D Point Clouds with Low Overlap.

hulaba/PLADE

PLADE: A Plane-based Descriptor for Point Cloud Registration with Small Overlap

hulaba/pywheat

Python library for simulation of wheat phenological development, crop growth and yield.

hulaba/RemoteCLIP

🛰️ Official repository of paper "RemoteCLIP: A Vision Language Foundation Model for Remote Sensing" (IEEE TGRS)

hulaba/SC2-PCR

SC2-PCR: A Second Order Spatial Compatibility for Efficient and Robust Point Cloud Registration (CVPR 2022)

hulaba/segment-anything

The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.

hulaba/segment-anything-2

The repository provides code for running inference with the Meta Segment Anything Model 2 (SAM 2), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.

hulaba/segment-geospatial

A Python package for segmenting geospatial data with the Segment Anything Model (SAM)

hulaba/slam_in_autonomous_driving

《自动驾驶中的SLAM技术》对应开源代码

hulaba/smile

Statistical Machine Intelligence & Learning Engine

hulaba/SSRS

hulaba/transcripts

hulaba/unlock-hf

解锁HuggingFace生态的百般用法

hulaba/VPFBR-L

A 3D point cloud registration and localization method based on voxel plane features