Papers with Code 아카이브

Cloud Detection

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법전체 데이터셋

하위 태스크

0

평가표

0

보존된 평가 기록

0

코드

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

https://github.com/IPL-UV/pvl8dagans

공식 코드

Cross-Sensor Adversarial Domain Adaptation of Landsat-8 and Proba-V images for Cloud Detection

https://github.com/Neooolee/WHUS2-CD

공식 코드

A lightweight deep learning based cloud detection method for Sentinel-2A imagery fusing multi-scale spectral and spatial features

https://github.com/SorourMo/95-Cloud-An-Extension-to-38-Cloud-Dataset

공식 코드

Cloud and Cloud Shadow Segmentation for Remote Sensing Imagery via Filtered Jaccard Loss Function and Parametric Augmentation

https://github.com/Soumyabrata/CloudSegNet

공식 코드

CloudSegNet: A Deep Network for Nychthemeron Cloud Image Segmentation

https://github.com/Soumyabrata/multilabel-unet

공식 코드

Multi-label Cloud Segmentation Using a Deep Network

https://github.com/aleksispi/ml-cloud-opt-thick

공식 코드

Creating and Leveraging a Synthetic Dataset of Cloud Optical Thickness Measures for Cloud Detection in MSI

https://github.com/anonymous-ai-for-earth/satellite-to-satellite-translation

공식 코드

Spectral Synthesis for Satellite-to-Satellite Translation

https://github.com/emit-sds/SpecTf

공식 코드

SpecTf: Transformers Enable Data-Driven Imaging Spectroscopy Cloud Detection

https://github.com/facebookresearch/deepmask

공식 코드

DeepMask: an algorithm for cloud and cloud shadow detection in optical satellite remote sensing images using deep residual network

https://github.com/hyeon-jo/interchange-transfer-kd

공식 코드

itKD: Interchange Transfer-based Knowledge Distillation for 3D Object Detection

https://github.com/jnyborg/fcd

공식 코드

Weakly-Supervised Cloud Detection with Fixed-Point GANs

https://github.com/kateduffy/maiac-emulator

공식 코드

A framework for deep learning emulation of numerical models with a case study in satellite remote sensing

https://github.com/kunzhan/hr-cloud-net

공식 코드

High-Resolution Cloud Detection Network

https://github.com/langekevin/mlspace_robustness

공식 코드

Machine Learning in Space: Surveying the Robustness of on-board ML models to Radiation

https://github.com/liying-xu/pgcs

공식 코드

PGCS: Physical Law embedded Generative Cloud Synthesis in Remote Sensing Images

https://github.com/lyhdet/ov-3det

공식 코드

Open-Vocabulary Point-Cloud Object Detection without 3D Annotation

https://github.com/microsoft/torchgeo

공식 코드

SSL4EO-L: Datasets and Foundation Models for Landsat Imagery

https://github.com/nasa-nccs-hpda/pytorch-caney

공식 코드

SatVision-TOA: A Geospatial Foundation Model for Coarse-Resolution All-Sky Remote Sensing Imagery

https://github.com/oshrout/GraVoS

공식 코드

GraVoS: Voxel Selection for 3D Point-Cloud Detection

https://github.com/ouyangjunyuan/pointcloud-3d-detector-tensorrt

공식 코드

Hierarchical Adaptive Voxel-guided Sampling for Real-time Applications in Large-scale Point Clouds

https://github.com/toelt-llc/cloud_segmentation_comparative

공식 코드

BenchCloudVision: A Benchmark Analysis of Deep Learning Approaches for Cloud Detection and Segmentation in Remote Sensing Imagery

https://github.com/xavierjiezou/pmaa

공식 코드

PMAA: A Progressive Multi-scale Attention Autoencoder Model for High-performance Cloud Removal from Multi-temporal Satellite Imagery

https://github.com/yitingqu/fakepcd

공식 코드

FAKEPCD: Fake Point Cloud Detection via Source Attribution

https://github.com/SorourMo/38-Cloud-A-Cloud-Segmentation-Dataset

Cloud-Net: An end-to-end Cloud Detection Algorithm for Landsat 8 Imagery

https://github.com/SorourMo/Cloud-Net-A-semantic-segmentation-CNN-for-cloud-detection

Cloud-Net: An end-to-end Cloud Detection Algorithm for Landsat 8 Imagery

https://github.com/dfrisinghelli/pysegcnn

Cloud-Net: An end-to-end Cloud Detection Algorithm for Landsat 8 Imagery

https://github.com/dveyarangi/cloud-net-plus

Cloud and Cloud Shadow Segmentation for Remote Sensing Imagery via Filtered Jaccard Loss Function and Parametric Augmentation

https://github.com/gterren/cloud_segmentation

Explicit Basis Function Kernel Methods for Cloud Segmentation in Infrared Sky Images

https://github.com/xavierjiezou/diffcr

PMAA: A Progressive Multi-scale Attention Autoencoder Model for High-performance Cloud Removal from Multi-temporal Satellite Imagery

https://github.com/zhu-xlab/ssl4eo-s12

SSL4EO-L: Datasets and Foundation Models for Landsat Imagery

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