Deep-Plant: Plant Classification with CNN/RNN. It consists of CAFFE/Tensorflow implementation of our PR-17, TIP-18 (HGO-CNN & PlantStructNet) and MalayaKew dataset.
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Updated
Mar 22, 2020 - Python
Deep-Plant: Plant Classification with CNN/RNN. It consists of CAFFE/Tensorflow implementation of our PR-17, TIP-18 (HGO-CNN & PlantStructNet) and MalayaKew dataset.
crop classification using deep learning on satellite images
Sen4AgriNet: A Sentinel-2 multi-year, multi-country benchmark dataset for crop classification and segmentation with deep learning
Winning Solutions from Crop Type Detection Competition at CV4A workshop, ICLR 2020
Information and scripts for the CropAndWeed Dataset
[RSE 2021] Crop mapping from image time series: deep learning with multi-scale label hierarchies
Code for the paper Multi Modal Deep Learning Based Crop Classification Using Multispectral and Multitemporal Satellite Imagery published in KDD Applied Data Science Track 2020
A dataset with Space (Sentinel-1/2) and Ground (street-level images) components, annotated with crop-type labels for agriculture monitoring.
Public repository of our IGARSS 2023 submission
Crop Classification of Remotely Sensed Images containing Multi Temporal and Multispectral Information
Python data pipeline to acquire, clean, and calculate vegetation indices from Sentinel-2 satellite image. Package is available only for our clients.
Crop classification in the Cauvery Delta Zone using a multichannel based transformer model
EuroCropsML is a ready-to-use benchmark dataset for few-shot crop type classification using Sentinel-2 imagery.
Public repository of our IGARSS 2023 submission
Source code from 2022 AI CUP Competition on Crop Status Monitoring by Image Recognition.
[TGRS21] Crop Classification under Varying Cloud Cover with Neural Ordinary Differential Equations
Public repository of our work in the search for an optimal multi-view crop classifier (considering encoder architectures and fusion strategies)
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