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Crop Classification

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하위 태스크

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평가표

5

보존된 평가 기록

18

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/0zgur0/ms-convSTAR

공식 코드

Crop mapping from image time series: deep learning with multi-scale label hierarchies

https://github.com/felixquinton1/deep-crop-rotation

공식 코드

Crop Rotation Modeling for Deep Learning-Based Parcel Classification from Satellite Time Series

https://github.com/fmenat/missingviews-study-eo

공식 코드

Impact Assessment of Missing Data in Model Predictions for Earth Observation Applications

https://github.com/fmenat/multiviewcropclassification

공식 코드

A Comparative Assessment of Multi-view fusion learning for Crop Classification

https://github.com/fmenat/mvlearning

공식 코드

Increasing the Robustness of Model Predictions to Missing Sensors in Earth Observation

https://github.com/fmenat/optimal-multiview-crop-classifier

공식 코드

In the Search for Optimal Multi-view Learning Models for Crop Classification with Global Remote Sensing Data

https://github.com/jnyborg/timematch

공식 코드

TimeMatch: Unsupervised Cross-Region Adaptation by Temporal Shift Estimation

https://github.com/jnyborg/tpe

공식 코드

Generalized Classification of Satellite Image Time Series with Thermal Positional Encoding

https://github.com/marccoru/elects

공식 코드

End-to-End Learned Early Classification of Time Series for In-Season Crop Type Mapping

https://github.com/momut1/lucasvision

공식 코드

Crop identification using deep learning on LUCAS crop cover photos

https://github.com/nandometzger/ODEcrop

공식 코드

Crop Classification under Varying Cloud Cover with Neural Ordinary Differential Equations

https://github.com/nasaharvest/presto

공식 코드

Lightweight, Pre-trained Transformers for Remote Sensing Timeseries

https://github.com/orion-ai-lab/s4a

공식 코드

A Sentinel-2 multi-year, multi-country benchmark dataset for crop classification and segmentation with deep learning

https://github.com/qinfengsama/compressor-based-crop-mapping

공식 코드

Low-Resource Crop Classification from Multi-Spectral Time Series Using Lossless Compressors

https://github.com/samar-khanna/cropmap

공식 코드

Activation Regression for Continuous Domain Generalization with Applications to Crop Classification

https://github.com/wangyuze-csu/joint_frp

공식 코드

A Joint Learning Framework with Feature Reconstruction and Prediction for Incomplete Satellite Image Time Series in Agricultural Semantic Segmentation

https://github.com/xiaoleiqinn/sitsmamba

공식 코드

SITSMamba for Crop Classification based on Satellite Image Time Series

https://github.com/yichiac/crop-type-transfer-learning

공식 코드

On the Generalizability of Foundation Models for Crop Type Mapping

https://github.com/BMIRDS/deepslide

Attention-Based Deep Neural Networks for Detection of Cancerous and Precancerous Esophagus Tissue on Histopathological Slides

https://github.com/JohnMBrandt/capsule-attention-networks

Spatio-temporal crop classification of low-resolution satellite imagery with capsule layers and distributed attention

https://github.com/fmenat/com-views

Increasing the Robustness of Model Predictions to Missing Sensors in Earth Observation

https://github.com/rtavenar/early_rnn

End-to-End Learned Early Classification of Time Series for In-Season Crop Type Mapping

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.