Fine-grained Hierarchical Crop Type Classification from Integrated Hyperspectral EnMAP Data and Multispectral Sentinel-2 Time Series: A Large-scale Dataset and Dual-stream Transformer Method | Paper Citation Record

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Fine-grained Hierarchical Crop Type Classification from Integrated Hyperspectral EnMAP Data and Multispectral Sentinel-2 Time Series: A Large-scale Dataset and Dual-stream Transformer Method write newline

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Fine-grained Hierarchical Crop Type Classification from Integrated Hyperspectral EnMAP Data and Multispectral Sentinel-2 Time Series: A Large-scale Dataset and Dual-stream Transformer Method write newline

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Fine-grained Hierarchical Crop Type Classification from Integrated Hyperspectral EnMAP Data and Multispectral Sentinel-2 Time Series: A Large-scale Dataset and Dual-stream Transformer Method write newline

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This paper cites title Pretrain a remote sensing foundation model by promoting intra-instance similarity.

Fine-grained Hierarchical Crop Type Classification from Integrated Hyperspectral EnMAP Data and Multispectral Sentinel-2 Time Series: A Large-scale Dataset and Dual-stream Transformer Method title Pretrain a remote sensing foundation model by promoting intra-instance similarity

Reference 4

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This paper cites title 220 band aviris hyperspectral image data set: June 12, 1992 indian pine test site 3.

Fine-grained Hierarchical Crop Type Classification from Integrated Hyperspectral EnMAP Data and Multispectral Sentinel-2 Time Series: A Large-scale Dataset and Dual-stream Transformer Method title 220 band aviris hyperspectral image data set: June 12, 1992 indian pine test site 3

Reference 5

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This paper cites title Mapping of crop types and crop sequences with combined time series of sentinel-1, sentinel-2 and landsat 8 data for germany.

Fine-grained Hierarchical Crop Type Classification from Integrated Hyperspectral EnMAP Data and Multispectral Sentinel-2 Time Series: A Large-scale Dataset and Dual-stream Transformer Method title Mapping of crop types and crop sequences with combined time series of sentinel-1, sentinel-2 and landsat 8 data for germany

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This paper cites title Random forests.

Fine-grained Hierarchical Crop Type Classification from Integrated Hyperspectral EnMAP Data and Multispectral Sentinel-2 Time Series: A Large-scale Dataset and Dual-stream Transformer Method title Random forests

Reference 7

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This paper cites title The enmap spaceborne imaging spectroscopy mission: Initial scientific results two years after launch.

Fine-grained Hierarchical Crop Type Classification from Integrated Hyperspectral EnMAP Data and Multispectral Sentinel-2 Time Series: A Large-scale Dataset and Dual-stream Transformer Method title The enmap spaceborne imaging spectroscopy mission: Initial scientific results two years after launch

Reference 8

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This paper cites title Adversarial instance augmentation for building change detection in remote sensing images.

Fine-grained Hierarchical Crop Type Classification from Integrated Hyperspectral EnMAP Data and Multispectral Sentinel-2 Time Series: A Large-scale Dataset and Dual-stream Transformer Method title Adversarial instance augmentation for building change detection in remote sensing images

Reference 9

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This paper cites title Rsmamba: Remote sensing image classification with state space model.

Fine-grained Hierarchical Crop Type Classification from Integrated Hyperspectral EnMAP Data and Multispectral Sentinel-2 Time Series: A Large-scale Dataset and Dual-stream Transformer Method title Rsmamba: Remote sensing image classification with state space model

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This paper cites title Dynamicvis: An efficient and general visual foundation model for remote sensing image understanding.

Fine-grained Hierarchical Crop Type Classification from Integrated Hyperspectral EnMAP Data and Multispectral Sentinel-2 Time Series: A Large-scale Dataset and Dual-stream Transformer Method title Dynamicvis: An efficient and general visual foundation model for remote sensing image understanding

Reference 11

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This paper cites title Rsprompter: Learning to prompt for remote sensing instance segmentation based on visual foundation model.

Fine-grained Hierarchical Crop Type Classification from Integrated Hyperspectral EnMAP Data and Multispectral Sentinel-2 Time Series: A Large-scale Dataset and Dual-stream Transformer Method title Rsprompter: Learning to prompt for remote sensing instance segmentation based on visual foundation model

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This paper cites title Time travelling pixels: Bitemporal features integration with foundation model for remote sensing image change detection.

Fine-grained Hierarchical Crop Type Classification from Integrated Hyperspectral EnMAP Data and Multispectral Sentinel-2 Time Series: A Large-scale Dataset and Dual-stream Transformer Method title Time travelling pixels: Bitemporal features integration with foundation model for remote sensing image change detection

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This paper cites title Mapping paddy rice cropping intensity and calendar in monsoon asia at 20 m resolution between 2018 and 2021 from multi-source satellite data using a sample-free algorithm.

Fine-grained Hierarchical Crop Type Classification from Integrated Hyperspectral EnMAP Data and Multispectral Sentinel-2 Time Series: A Large-scale Dataset and Dual-stream Transformer Method title Mapping paddy rice cropping intensity and calendar in monsoon asia at 20 m resolution between 2018 and 2021 from multi-source satellite data using a sample-free algorithm

Reference 14

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This paper cites title Using prisma hyperspectral data for land cover classification with artificial intelligence support.

Fine-grained Hierarchical Crop Type Classification from Integrated Hyperspectral EnMAP Data and Multispectral Sentinel-2 Time Series: A Large-scale Dataset and Dual-stream Transformer Method title Using prisma hyperspectral data for land cover classification with artificial intelligence support

Reference 15

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This paper cites title Improved regularization of convolutional neural networks with cutout.

Fine-grained Hierarchical Crop Type Classification from Integrated Hyperspectral EnMAP Data and Multispectral Sentinel-2 Time Series: A Large-scale Dataset and Dual-stream Transformer Method title Improved regularization of convolutional neural networks with cutout

Reference 16

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This paper cites title Early season mapping of winter wheat in china based on landsat and sentinel images.

Fine-grained Hierarchical Crop Type Classification from Integrated Hyperspectral EnMAP Data and Multispectral Sentinel-2 Time Series: A Large-scale Dataset and Dual-stream Transformer Method title Early season mapping of winter wheat in china based on landsat and sentinel images

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This paper cites title An image is worth 16x16 words: Transformers for image recognition at scale.

Fine-grained Hierarchical Crop Type Classification from Integrated Hyperspectral EnMAP Data and Multispectral Sentinel-2 Time Series: A Large-scale Dataset and Dual-stream Transformer Method title An image is worth 16x16 words: Transformers for image recognition at scale

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This paper cites title A comprehensive review of rice mapping from satellite data: Algorithms, product characteristics and consistency assessment.

Fine-grained Hierarchical Crop Type Classification from Integrated Hyperspectral EnMAP Data and Multispectral Sentinel-2 Time Series: A Large-scale Dataset and Dual-stream Transformer Method title A comprehensive review of rice mapping from satellite data: Algorithms, product characteristics and consistency assessment

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This paper cites title Generating an annual 30m rice cover product for monsoon asia (2018-2023) using harmonized landsat and sentinel-2 data and the nasa-ibm geospatial foundation model.

Fine-grained Hierarchical Crop Type Classification from Integrated Hyperspectral EnMAP Data and Multispectral Sentinel-2 Time Series: A Large-scale Dataset and Dual-stream Transformer Method title Generating an annual 30m rice cover product for monsoon asia (2018-2023) using harmonized landsat and sentinel-2 data and the nasa-ibm geospatial foundation model

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Fine-grained Hierarchical Crop Type Classification from Integrated Hyperspectral EnMAP Data and Multispectral Sentinel-2 Time Series: A Large-scale Dataset and Dual-stream Transformer Method title Crop type classification by desis hyperspectral imagery and machine learning algorithms

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Fine-grained Hierarchical Crop Type Classification from Integrated Hyperspectral EnMAP Data and Multispectral Sentinel-2 Time Series: A Large-scale Dataset and Dual-stream Transformer Method title 3d cnns with adaptive temporal feature resolutions

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Fine-grained Hierarchical Crop Type Classification from Integrated Hyperspectral EnMAP Data and Multispectral Sentinel-2 Time Series: A Large-scale Dataset and Dual-stream Transformer Method title Cat: Center attention transformer with stratified spatial-spectral token for hyperspectral image classification

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Fine-grained Hierarchical Crop Type Classification from Integrated Hyperspectral EnMAP Data and Multispectral Sentinel-2 Time Series: A Large-scale Dataset and Dual-stream Transformer Method title Three-dimensional singular spectrum analysis for precise land cover classification from uav-borne hyperspectral benchmark datasets

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Fine-grained Hierarchical Crop Type Classification from Integrated Hyperspectral EnMAP Data and Multispectral Sentinel-2 Time Series: A Large-scale Dataset and Dual-stream Transformer Method title In-season and dynamic crop mapping using 3d convolution neural networks and sentinel-2 time series

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Fine-grained Hierarchical Crop Type Classification from Integrated Hyperspectral EnMAP Data and Multispectral Sentinel-2 Time Series: A Large-scale Dataset and Dual-stream Transformer Method title Recurrent neural networks and long short-term memory networks: Tutorial and survey

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This paper cites title Deep learning techniques for hyperspectral image analysis in agriculture: A review.

Fine-grained Hierarchical Crop Type Classification from Integrated Hyperspectral EnMAP Data and Multispectral Sentinel-2 Time Series: A Large-scale Dataset and Dual-stream Transformer Method title Deep learning techniques for hyperspectral image analysis in agriculture: A review

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Fine-grained Hierarchical Crop Type Classification from Integrated Hyperspectral EnMAP Data and Multispectral Sentinel-2 Time Series: A Large-scale Dataset and Dual-stream Transformer Method title Deepseek-r1: Incentivizing reasoning capability in llms via reinforcement learning

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Fine-grained Hierarchical Crop Type Classification from Integrated Hyperspectral EnMAP Data and Multispectral Sentinel-2 Time Series: A Large-scale Dataset and Dual-stream Transformer Method title Nesea-rice10: high-resolution annual paddy rice maps for northeast and southeast asia from 2017 to 2019

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This paper cites title Can spatiotemporal 3d cnns retrace the history of 2d cnns and imagenet? In: booktitle Proceedings of the IEEE conference on Computer Vision and Pattern Recognition.

Fine-grained Hierarchical Crop Type Classification from Integrated Hyperspectral EnMAP Data and Multispectral Sentinel-2 Time Series: A Large-scale Dataset and Dual-stream Transformer Method title Can spatiotemporal 3d cnns retrace the history of 2d cnns and imagenet? In: booktitle Proceedings of the IEEE conference on Computer Vision and Pattern Recognition

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Fine-grained Hierarchical Crop Type Classification from Integrated Hyperspectral EnMAP Data and Multispectral Sentinel-2 Time Series: A Large-scale Dataset and Dual-stream Transformer Method title Deep residual learning for image recognition

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Fine-grained Hierarchical Crop Type Classification from Integrated Hyperspectral EnMAP Data and Multispectral Sentinel-2 Time Series: A Large-scale Dataset and Dual-stream Transformer Method title Support vector machines

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Fine-grained Hierarchical Crop Type Classification from Integrated Hyperspectral EnMAP Data and Multispectral Sentinel-2 Time Series: A Large-scale Dataset and Dual-stream Transformer Method title Mdas: a new multimodal benchmark dataset for remote sensing

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Fine-grained Hierarchical Crop Type Classification from Integrated Hyperspectral EnMAP Data and Multispectral Sentinel-2 Time Series: A Large-scale Dataset and Dual-stream Transformer Method title Pixel shuffling is all you need: spatially aware convmixer for dense prediction tasks

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This paper cites title Remote-sensing data and deep-learning techniques in crop mapping and yield prediction: A systematic review.

Fine-grained Hierarchical Crop Type Classification from Integrated Hyperspectral EnMAP Data and Multispectral Sentinel-2 Time Series: A Large-scale Dataset and Dual-stream Transformer Method title Remote-sensing data and deep-learning techniques in crop mapping and yield prediction: A systematic review

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Fine-grained Hierarchical Crop Type Classification from Integrated Hyperspectral EnMAP Data and Multispectral Sentinel-2 Time Series: A Large-scale Dataset and Dual-stream Transformer Method title Deep learning

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Fine-grained Hierarchical Crop Type Classification from Integrated Hyperspectral EnMAP Data and Multispectral Sentinel-2 Time Series: A Large-scale Dataset and Dual-stream Transformer Method title Whu-ohs: A benchmark dataset for large-scale hersepctral image classification

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Fine-grained Hierarchical Crop Type Classification from Integrated Hyperspectral EnMAP Data and Multispectral Sentinel-2 Time Series: A Large-scale Dataset and Dual-stream Transformer Method title Geographical knowledge-driven representation learning for remote sensing images

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Fine-grained Hierarchical Crop Type Classification from Integrated Hyperspectral EnMAP Data and Multispectral Sentinel-2 Time Series: A Large-scale Dataset and Dual-stream Transformer Method title Agrifm: A multi-source temporal remote sensing foundation model for crop mapping

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This paper cites title Asiawheat: The first asian 250-m annual fractional wheat cover time series (2001-2023) using convolutional neural networks and transformer models.

Fine-grained Hierarchical Crop Type Classification from Integrated Hyperspectral EnMAP Data and Multispectral Sentinel-2 Time Series: A Large-scale Dataset and Dual-stream Transformer Method title Asiawheat: The first asian 250-m annual fractional wheat cover time series (2001-2023) using convolutional neural networks and transformer models

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This paper cites title Advances in high-resolution land surface satellite products: A comprehensive review of inversion algorithms, products and challenges.

Fine-grained Hierarchical Crop Type Classification from Integrated Hyperspectral EnMAP Data and Multispectral Sentinel-2 Time Series: A Large-scale Dataset and Dual-stream Transformer Method title Advances in high-resolution land surface satellite products: A comprehensive review of inversion algorithms, products and challenges

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Fine-grained Hierarchical Crop Type Classification from Integrated Hyperspectral EnMAP Data and Multispectral Sentinel-2 Time Series: A Large-scale Dataset and Dual-stream Transformer Method title Diverse hyperspectral remote sensing image synthesis with diffusion models

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T06:02:02.102230Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 51bd159a-de87-426f-a64d-c8c7aa9f5419 · outbound

This paper cites title Swin transformer: Hierarchical vision transformer using shifted windows.

Fine-grained Hierarchical Crop Type Classification from Integrated Hyperspectral EnMAP Data and Multispectral Sentinel-2 Time Series: A Large-scale Dataset and Dual-stream Transformer Method title Swin transformer: Hierarchical vision transformer using shifted windows

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T06:02:02.086640Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation f22218f1-7c3b-44a0-92cc-fe704cd1cc33 · outbound

This paper cites title Video swin transformer.

Fine-grained Hierarchical Crop Type Classification from Integrated Hyperspectral EnMAP Data and Multispectral Sentinel-2 Time Series: A Large-scale Dataset and Dual-stream Transformer Method title Video swin transformer

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T06:02:02.072928Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 528991a0-00da-47b0-8bbf-307fd7a1c45b · outbound

This paper cites title Fully convolutional networks for semantic segmentation.

Fine-grained Hierarchical Crop Type Classification from Integrated Hyperspectral EnMAP Data and Multispectral Sentinel-2 Time Series: A Large-scale Dataset and Dual-stream Transformer Method title Fully convolutional networks for semantic segmentation

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T06:02:02.058976Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 1dade3f9-94eb-4894-8d79-bd4bfc5eb51a · outbound

This paper cites title A time-weighted dynamic time warping method for land-use and land-cover mapping.

Fine-grained Hierarchical Crop Type Classification from Integrated Hyperspectral EnMAP Data and Multispectral Sentinel-2 Time Series: A Large-scale Dataset and Dual-stream Transformer Method title A time-weighted dynamic time warping method for land-use and land-cover mapping

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T06:02:02.043978Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 4c485edb-c21f-4beb-9002-6bfe564f114a · outbound

This paper cites title Land use and land cover classification with hyperspectral data: A comprehensive review of methods, challenges and future directions.

Fine-grained Hierarchical Crop Type Classification from Integrated Hyperspectral EnMAP Data and Multispectral Sentinel-2 Time Series: A Large-scale Dataset and Dual-stream Transformer Method title Land use and land cover classification with hyperspectral data: A comprehensive review of methods, challenges and future directions

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T06:02:02.026234Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 5b98aad8-0796-4938-aa0a-867f54343a02 · outbound

This paper cites title The land parcel identification system: A useful tool to determine the eligibility of agricultural land—but its management could be further improved.

Fine-grained Hierarchical Crop Type Classification from Integrated Hyperspectral EnMAP Data and Multispectral Sentinel-2 Time Series: A Large-scale Dataset and Dual-stream Transformer Method title The land parcel identification system: A useful tool to determine the eligibility of agricultural land—but its management could be further improved

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T06:02:02.007289Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 4d0ec134-1305-4af6-800f-0e4a9506a995 · outbound

This paper cites title A twenty-year dataset of high-resolution maize distribution in china.

Fine-grained Hierarchical Crop Type Classification from Integrated Hyperspectral EnMAP Data and Multispectral Sentinel-2 Time Series: A Large-scale Dataset and Dual-stream Transformer Method title A twenty-year dataset of high-resolution maize distribution in china

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T06:02:01.991840Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 11414281-0f04-4e83-b268-76af70e98c41 · outbound

This paper cites title 2018 ieee grss data fusion challenge – fusion of multispectral lidar and hyperspectral data.

Fine-grained Hierarchical Crop Type Classification from Integrated Hyperspectral EnMAP Data and Multispectral Sentinel-2 Time Series: A Large-scale Dataset and Dual-stream Transformer Method title 2018 ieee grss data fusion challenge – fusion of multispectral lidar and hyperspectral data

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-07T06:02:01.122654Z

Source-reported events for the cited work

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Observation 3ebbd92c-b60f-482f-9ca6-34609c2a7cf3 · outbound

This paper cites title Maps of cropping patterns in china during 2015--2021.

Fine-grained Hierarchical Crop Type Classification from Integrated Hyperspectral EnMAP Data and Multispectral Sentinel-2 Time Series: A Large-scale Dataset and Dual-stream Transformer Method title Maps of cropping patterns in china during 2015--2021

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T06:02:01.972760Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 1a44c757-2828-4634-910b-3c243b962599 · outbound

This paper cites title End-to-end learned early classification of time series for in-season crop type mapping.

Fine-grained Hierarchical Crop Type Classification from Integrated Hyperspectral EnMAP Data and Multispectral Sentinel-2 Time Series: A Large-scale Dataset and Dual-stream Transformer Method title End-to-end learned early classification of time series for in-season crop type mapping

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T06:02:01.958237Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 51dbd89c-ebaf-4a1c-8480-f2fde1862e1c · outbound

This paper cites title Breizhcrops: A time series dataset for crop type mapping.

Fine-grained Hierarchical Crop Type Classification from Integrated Hyperspectral EnMAP Data and Multispectral Sentinel-2 Time Series: A Large-scale Dataset and Dual-stream Transformer Method title Breizhcrops: A time series dataset for crop type mapping

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T06:02:01.941374Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 8fcea0c8-7b3d-4cea-ae5a-41143474218f · outbound

This paper cites title Eurocrops: The largest harmonized open crop dataset across the european union.

Fine-grained Hierarchical Crop Type Classification from Integrated Hyperspectral EnMAP Data and Multispectral Sentinel-2 Time Series: A Large-scale Dataset and Dual-stream Transformer Method title Eurocrops: The largest harmonized open crop dataset across the european union

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T06:02:01.925698Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 252bc7b5-e130-405f-9792-ea510646a472 · outbound

This paper cites title Remote sensing for precision agriculture: Sentinel-2 improved features and applications.

Fine-grained Hierarchical Crop Type Classification from Integrated Hyperspectral EnMAP Data and Multispectral Sentinel-2 Time Series: A Large-scale Dataset and Dual-stream Transformer Method title Remote sensing for precision agriculture: Sentinel-2 improved features and applications

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T06:02:01.911431Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 6897505b-10f3-4913-a12e-c0c2d9c2b683 · outbound

This paper cites title Agrisen-cog, a multicountry, multitemporal large-scale sentinel-2 benchmark dataset for crop mapping using deep learning.

Fine-grained Hierarchical Crop Type Classification from Integrated Hyperspectral EnMAP Data and Multispectral Sentinel-2 Time Series: A Large-scale Dataset and Dual-stream Transformer Method title Agrisen-cog, a multicountry, multitemporal large-scale sentinel-2 benchmark dataset for crop mapping using deep learning

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T06:02:01.896369Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation ec21f3f8-194b-48da-82d0-be1a849a7eea · outbound

This paper cites title Real-time single image and video super-resolution using an efficient sub-pixel convolutional neural network.

Fine-grained Hierarchical Crop Type Classification from Integrated Hyperspectral EnMAP Data and Multispectral Sentinel-2 Time Series: A Large-scale Dataset and Dual-stream Transformer Method title Real-time single image and video super-resolution using an efficient sub-pixel convolutional neural network

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T06:02:01.879033Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 0c0d6513-e6cd-4bbb-8fd1-bf6e08ece02e · outbound

This paper cites title Meta-weight-net: Learning an explicit mapping for sample weighting.

Fine-grained Hierarchical Crop Type Classification from Integrated Hyperspectral EnMAP Data and Multispectral Sentinel-2 Time Series: A Large-scale Dataset and Dual-stream Transformer Method title Meta-weight-net: Learning an explicit mapping for sample weighting

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T06:02:01.864060Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 1dcf2347-aac9-4820-998c-5654a218cf44 · outbound

This paper cites title The enmap imaging spectroscopy mission towards operations.

Fine-grained Hierarchical Crop Type Classification from Integrated Hyperspectral EnMAP Data and Multispectral Sentinel-2 Time Series: A Large-scale Dataset and Dual-stream Transformer Method title The enmap imaging spectroscopy mission towards operations

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T06:02:01.849631Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 740a0d86-05f9-4818-bc46-557ff92dd470 · outbound

This paper cites title A sentinel-2 multiyear, multicountry benchmark dataset for crop classification and segmentation with deep learning.

Fine-grained Hierarchical Crop Type Classification from Integrated Hyperspectral EnMAP Data and Multispectral Sentinel-2 Time Series: A Large-scale Dataset and Dual-stream Transformer Method title A sentinel-2 multiyear, multicountry benchmark dataset for crop classification and segmentation with deep learning

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T06:02:01.834086Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 11ed3702-e471-42b1-b268-8f8bac1a18b0 · outbound

This paper cites title Crop mapping from image time series: Deep learning with multi-scale label hierarchies.

Fine-grained Hierarchical Crop Type Classification from Integrated Hyperspectral EnMAP Data and Multispectral Sentinel-2 Time Series: A Large-scale Dataset and Dual-stream Transformer Method title Crop mapping from image time series: Deep learning with multi-scale label hierarchies

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T06:02:01.818463Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 2201fc14-bc22-4c71-a92a-2ce033fd030a · outbound

This paper cites title Worldcereal: a dynamic open-source system for global-scale, seasonal, and reproducible crop and irrigation mapping.

Fine-grained Hierarchical Crop Type Classification from Integrated Hyperspectral EnMAP Data and Multispectral Sentinel-2 Time Series: A Large-scale Dataset and Dual-stream Transformer Method title Worldcereal: a dynamic open-source system for global-scale, seasonal, and reproducible crop and irrigation mapping

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T06:02:01.803426Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 98421425-30b9-4528-90e7-bd6044d52c7c · outbound

This paper cites title Attention is all you need.

Fine-grained Hierarchical Crop Type Classification from Integrated Hyperspectral EnMAP Data and Multispectral Sentinel-2 Time Series: A Large-scale Dataset and Dual-stream Transformer Method title Attention is all you need

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T06:02:01.788488Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation c582ea8e-bcb8-4ba5-aeae-07b7f5e9932a · outbound

This paper cites title Remote sensing for agriculture in the era of industry 5.0--a survey.

Fine-grained Hierarchical Crop Type Classification from Integrated Hyperspectral EnMAP Data and Multispectral Sentinel-2 Time Series: A Large-scale Dataset and Dual-stream Transformer Method title Remote sensing for agriculture in the era of industry 5.0--a survey

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T06:02:01.769468Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 691a7657-d034-4138-b756-4e324d57941b · outbound

This paper cites title Hyper-es2t: efficient spatial--spectral transformer for the classification of hyperspectral remote sensing images.

Fine-grained Hierarchical Crop Type Classification from Integrated Hyperspectral EnMAP Data and Multispectral Sentinel-2 Time Series: A Large-scale Dataset and Dual-stream Transformer Method title Hyper-es2t: efficient spatial--spectral transformer for the classification of hyperspectral remote sensing images

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T06:02:01.742867Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 0fbd0017-d7a7-4fa5-bb43-4eacab4a8079 · outbound

This paper cites title Timesen2crop: A million labeled samples dataset of sentinel 2 image time series for crop-type classification.

Fine-grained Hierarchical Crop Type Classification from Integrated Hyperspectral EnMAP Data and Multispectral Sentinel-2 Time Series: A Large-scale Dataset and Dual-stream Transformer Method title Timesen2crop: A million labeled samples dataset of sentinel 2 image time series for crop-type classification

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T06:02:01.722333Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation aeaf408d-e2bc-4693-a746-2b326fa9fbe0 · outbound

This paper cites title Remote sensing for agricultural applications: A meta-review.

Fine-grained Hierarchical Crop Type Classification from Integrated Hyperspectral EnMAP Data and Multispectral Sentinel-2 Time Series: A Large-scale Dataset and Dual-stream Transformer Method title Remote sensing for agricultural applications: A meta-review

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T06:02:01.706868Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 89ef7a81-aa39-4c5f-a955-f1afcf7f2148 · outbound

This paper cites title The 10-m crop type maps in northeast china during 2017--2019.

Fine-grained Hierarchical Crop Type Classification from Integrated Hyperspectral EnMAP Data and Multispectral Sentinel-2 Time Series: A Large-scale Dataset and Dual-stream Transformer Method title The 10-m crop type maps in northeast china during 2017--2019

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T06:02:01.690657Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation dcaf300a-bce4-43ce-b6f9-4213389ddf17 · outbound

This paper cites title Deep learning in environmental remote sensing: Achievements and challenges.

Fine-grained Hierarchical Crop Type Classification from Integrated Hyperspectral EnMAP Data and Multispectral Sentinel-2 Time Series: A Large-scale Dataset and Dual-stream Transformer Method title Deep learning in environmental remote sensing: Achievements and challenges

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T06:02:01.670379Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation fcc8f78c-3621-45dc-986f-5dfae6fd9353 · outbound

This paper cites title Sanet: A self-attention network for agricultural hyperspectral image classification.

Fine-grained Hierarchical Crop Type Classification from Integrated Hyperspectral EnMAP Data and Multispectral Sentinel-2 Time Series: A Large-scale Dataset and Dual-stream Transformer Method title Sanet: A self-attention network for agricultural hyperspectral image classification

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T06:02:01.653979Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 9e4b92e5-aafa-45a9-a663-38e2cbfd1c39 · outbound

This paper cites title A review on edge large language models: Design, execution, and applications.

Fine-grained Hierarchical Crop Type Classification from Integrated Hyperspectral EnMAP Data and Multispectral Sentinel-2 Time Series: A Large-scale Dataset and Dual-stream Transformer Method title A review on edge large language models: Design, execution, and applications

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T06:02:01.638926Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation ca9c91f8-5d8c-49ee-9f41-f5a492b0e182 · outbound

This paper cites title Spatiotemporal fusion in 3d cnns: A probabilistic view.

Fine-grained Hierarchical Crop Type Classification from Integrated Hyperspectral EnMAP Data and Multispectral Sentinel-2 Time Series: A Large-scale Dataset and Dual-stream Transformer Method title Spatiotemporal fusion in 3d cnns: A probabilistic view

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T06:02:01.601427Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation deeb44f8-a45d-414d-af8d-6551bbdf34d6 · outbound

This paper cites title Deep learning in remote sensing: A comprehensive review and list of resources.

Fine-grained Hierarchical Crop Type Classification from Integrated Hyperspectral EnMAP Data and Multispectral Sentinel-2 Time Series: A Large-scale Dataset and Dual-stream Transformer Method title Deep learning in remote sensing: A comprehensive review and list of resources

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T06:02:01.581611Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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