Paper Citation Record · LEDGER

Knowledge Transfer and Domain Adaptation for Fine-Grained Remote Sensing Image Segmentation

As of 12 August 2026, this Paper Citation Record lists 37 of 37 outbound references and 0 inbound Pith citation observations for arXiv:2412.06664.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2412.06664 v3

Coverage vector

measured 37 of 37 reference resolution

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Source: paper_references, paper_reference_links, observed 2026-08-11T19:29:59.424222Z

measured 37 of 37 standing notices

One-hop event checks from named stored sources.

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measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

37 of 37 outbound references displayed

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External citation measurements

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Outbound references

Observation d3c14766-7062-4e06-9d9f-6a05d028e725 · outbound

This paper cites Large-scale land cover mapping with fine-grained classes via class-aware semi- supervised semantic segmentation,.

Knowledge Transfer and Domain Adaptation for Fine-Grained Remote Sensing Image Segmentation Large-scale land cover mapping with fine-grained classes via class-aware semi- supervised semantic segmentation,

Reference 1

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Observation 1871ead4-74da-449f-9a98-d2ade1eacb85 · outbound

This paper cites Fine-grained recognition for oriented ship against complex scenes in optical remote sensing images,.

Knowledge Transfer and Domain Adaptation for Fine-Grained Remote Sensing Image Segmentation Fine-grained recognition for oriented ship against complex scenes in optical remote sensing images,

Reference 2

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Observation f26fe480-9b04-4cd3-9067-bc2633b9d79f · outbound

This paper cites Multiattention network for semantic segmentation of fine-resolution remote sensing images,.

Knowledge Transfer and Domain Adaptation for Fine-Grained Remote Sensing Image Segmentation Multiattention network for semantic segmentation of fine-resolution remote sensing images,

Reference 3

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Observation d8a62df9-dca3-4cb5-99a5-266e293e66a6 · outbound

This paper cites Fully convolu- tional networks for semantic segmentation,.

Knowledge Transfer and Domain Adaptation for Fine-Grained Remote Sensing Image Segmentation Fully convolu- tional networks for semantic segmentation,

Reference 4

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Observation f88899b6-4d78-4dfb-baea-54eebb82ff79 · outbound

This paper cites U-net: Con- volutional networks for biomedical image segmentation,.

Knowledge Transfer and Domain Adaptation for Fine-Grained Remote Sensing Image Segmentation U-net: Con- volutional networks for biomedical image segmentation,

Reference 5

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Observation 8aca351a-4b8e-4b35-9631-c54be68cf678 · outbound

This paper cites Pyramid scene parsing network,.

Knowledge Transfer and Domain Adaptation for Fine-Grained Remote Sensing Image Segmentation Pyramid scene parsing network,

Reference 6

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Observation 7ea8211e-eb65-42b7-b7fb-5b65d2e336c0 · outbound

This paper cites Encoder-decoder with atrous separable convolution for semantic image segmentation,.

Knowledge Transfer and Domain Adaptation for Fine-Grained Remote Sensing Image Segmentation Encoder-decoder with atrous separable convolution for semantic image segmentation,

Reference 7

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Observation 9e3ca545-9dfe-427e-8ad6-23dddb0a75af · outbound

This paper cites PMAA: A progressive multi-scale attention autoencoder model for high-performance cloud removal from multi-temporal satellite imagery,.

Knowledge Transfer and Domain Adaptation for Fine-Grained Remote Sensing Image Segmentation PMAA: A progressive multi-scale attention autoencoder model for high-performance cloud removal from multi-temporal satellite imagery,

Reference 8

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Observation eb5907ff-6011-42c8-8fd0-7dff15ecf184 · outbound

This paper cites Diffcr: A fast conditional diffusion framework for cloud removal from optical satellite images,.

Knowledge Transfer and Domain Adaptation for Fine-Grained Remote Sensing Image Segmentation Diffcr: A fast conditional diffusion framework for cloud removal from optical satellite images,

Reference 9

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Observation 226db8ee-0be3-40e2-ab5c-6ef57f44d83b · outbound

This paper cites Sam-clip: Merging vision foundation models towards semantic and spatial understanding,.

Knowledge Transfer and Domain Adaptation for Fine-Grained Remote Sensing Image Segmentation Sam-clip: Merging vision foundation models towards semantic and spatial understanding,

Reference 10

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Observation b56ccefb-07b5-4372-8701-b7f010c50193 · outbound

This paper cites DI- NOv2: Learning Robust Visual Features without Supervision,.

Knowledge Transfer and Domain Adaptation for Fine-Grained Remote Sensing Image Segmentation DI- NOv2: Learning Robust Visual Features without Supervision,

Reference 11

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Observation 6c7aef1f-8648-48ad-97dd-ff7837c0feff · outbound

This paper cites Learning transferable visual models from natural language supervision,.

Knowledge Transfer and Domain Adaptation for Fine-Grained Remote Sensing Image Segmentation Learning transferable visual models from natural language supervision,

Reference 12

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Observation 399c5caa-4e12-4933-96fc-1e4519da2dc4 · outbound

This paper cites Iianet: An intra- and inter-modality attention network for audio-visual speech separation,.

Knowledge Transfer and Domain Adaptation for Fine-Grained Remote Sensing Image Segmentation Iianet: An intra- and inter-modality attention network for audio-visual speech separation,

Reference 13

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Observation 8bec45be-0383-4cac-a54f-3253111b54ec · outbound

This paper cites Imagenet large scale visual recognition challenge,.

Knowledge Transfer and Domain Adaptation for Fine-Grained Remote Sensing Image Segmentation Imagenet large scale visual recognition challenge,

Reference 14

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Observation 40eb0914-f93a-4161-b87c-4c7babdadedb · outbound

This paper cites Segformer: Simple and efficient design for semantic segmentation with transformers,.

Knowledge Transfer and Domain Adaptation for Fine-Grained Remote Sensing Image Segmentation Segformer: Simple and efficient design for semantic segmentation with transformers,

Reference 15

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Observation 024ea7df-d68c-4cf7-945e-1cecd82a6d07 · outbound

This paper cites Masked-attention mask transformer for universal image segmentation,.

Knowledge Transfer and Domain Adaptation for Fine-Grained Remote Sensing Image Segmentation Masked-attention mask transformer for universal image segmentation,

Reference 16

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Observation b8070d74-3a5e-484b-9e5b-9b367d2aac94 · outbound

This paper cites Cdnet: Cnn-based cloud detection for remote sensing imagery,.

Knowledge Transfer and Domain Adaptation for Fine-Grained Remote Sensing Image Segmentation Cdnet: Cnn-based cloud detection for remote sensing imagery,

Reference 17

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This paper cites Cdnetv2: Cnn-based cloud detection for remote sensing imagery with cloud-snow coexistence,.

Knowledge Transfer and Domain Adaptation for Fine-Grained Remote Sensing Image Segmentation Cdnetv2: Cnn-based cloud detection for remote sensing imagery with cloud-snow coexistence,

Reference 18

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Observation 49a276ab-5b7f-41fc-bc68-5d5980931e6f · outbound

This paper cites Distilling the knowledge in a neural network,.

Knowledge Transfer and Domain Adaptation for Fine-Grained Remote Sensing Image Segmentation Distilling the knowledge in a neural network,

Reference 19

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Observation 17dcc660-ec83-4859-86e7-edcabd0db6c1 · outbound

This paper cites Faster Segment Anything: Towards Lightweight SAM for Mobile Applications.

Knowledge Transfer and Domain Adaptation for Fine-Grained Remote Sensing Image Segmentation Faster Segment Anything: Towards Lightweight SAM for Mobile Applications

Reference 20

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Observation 03e3553e-5979-4442-9ff7-1213f462e3fd · outbound

This paper cites Efficientsam: Leveraged masked image pretraining for efficient segment anything,.

Knowledge Transfer and Domain Adaptation for Fine-Grained Remote Sensing Image Segmentation Efficientsam: Leveraged masked image pretraining for efficient segment anything,

Reference 21

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This paper cites Segment anything,.

Knowledge Transfer and Domain Adaptation for Fine-Grained Remote Sensing Image Segmentation Segment anything,

Reference 22

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Observation 45fad3de-0eaa-4ff5-8285-a4cf724f9019 · outbound

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

Knowledge Transfer and Domain Adaptation for Fine-Grained Remote Sensing Image Segmentation An image is worth 16x16 words: Transformers for image recognition at scale,

Reference 23

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Observation 7827be9b-18aa-43e7-9c09-72dce0a5e5cc · outbound

This paper cites Masked autoencoders are scalable vision learners,.

Knowledge Transfer and Domain Adaptation for Fine-Grained Remote Sensing Image Segmentation Masked autoencoders are scalable vision learners,

Reference 24

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Observation 5c39b398-7783-4f5d-be50-8fbcbfa983ea · outbound

This paper cites Adapting vision foundation models for robust cloud segmentation in remote sensing images,.

Knowledge Transfer and Domain Adaptation for Fine-Grained Remote Sensing Image Segmentation Adapting vision foundation models for robust cloud segmentation in remote sensing images,

Reference 25

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This paper cites Eurosat: A novel dataset and deep learning benchmark for land use and land cover classification,.

Knowledge Transfer and Domain Adaptation for Fine-Grained Remote Sensing Image Segmentation Eurosat: A novel dataset and deep learning benchmark for land use and land cover classification,

Reference 26

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This paper cites Land-cover classification with high-resolution remote sensing images using transferable deep models,.

Knowledge Transfer and Domain Adaptation for Fine-Grained Remote Sensing Image Segmentation Land-cover classification with high-resolution remote sensing images using transferable deep models,

Reference 27

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Observation 51a38ae7-3360-45d9-aa83-aaf4a6d723cf · outbound

This paper cites Landcover.ai: Dataset for automatic mapping of buildings, woodlands, water and roads from aerial imagery,.

Knowledge Transfer and Domain Adaptation for Fine-Grained Remote Sensing Image Segmentation Landcover.ai: Dataset for automatic mapping of buildings, woodlands, water and roads from aerial imagery,

Reference 28

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Observation 08fec5f1-6f9f-4df9-a101-c0fc9cbb261a · outbound

This paper cites Algorithms for semantic segmentation of multispectral remote sensing imagery using deep learning,.

Knowledge Transfer and Domain Adaptation for Fine-Grained Remote Sensing Image Segmentation Algorithms for semantic segmentation of multispectral remote sensing imagery using deep learning,

Reference 29

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Observation 7da717b0-1b74-44e7-9e54-a172027c977f · outbound

This paper cites Cloud detec- tion algorithm comparison and validation for operational landsat data products,.

Knowledge Transfer and Domain Adaptation for Fine-Grained Remote Sensing Image Segmentation Cloud detec- tion algorithm comparison and validation for operational landsat data products,

Reference 30

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Observation 03a828b2-2423-4f1c-bd56-a18b748bac3b · outbound

This paper cites Unified perceptual parsing for scene understanding,.

Knowledge Transfer and Domain Adaptation for Fine-Grained Remote Sensing Image Segmentation Unified perceptual parsing for scene understanding,

Reference 31

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Observation c340cf0f-ad82-43b1-bc97-726b11d68430 · outbound

This paper cites Decoupled weight decay regulariza- tion,.

Knowledge Transfer and Domain Adaptation for Fine-Grained Remote Sensing Image Segmentation Decoupled weight decay regulariza- tion,

Reference 32

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Observation aca91790-254b-4c16-b80d-d4cbe87a521c · outbound

This paper cites Remote sensing image cloud detection using a shallow convolutional neural network,.

Knowledge Transfer and Domain Adaptation for Fine-Grained Remote Sensing Image Segmentation Remote sensing image cloud detection using a shallow convolutional neural network,

Reference 33

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Observation 9b659f5c-5ce6-4ec7-875a-666182376c7d · outbound

This paper cites Mcdnet: Multilevel cloud detection network for remote sensing images based on dual-perspective change-guided and multi-scale feature fusion,.

Knowledge Transfer and Domain Adaptation for Fine-Grained Remote Sensing Image Segmentation Mcdnet: Multilevel cloud detection network for remote sensing images based on dual-perspective change-guided and multi-scale feature fusion,

Reference 34

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Observation 41673742-6885-47e7-a4fc-9c583d499b67 · outbound

This paper cites Cloudsen12, a global dataset for semantic understanding of cloud and cloud shadow in sentinel-2,.

Knowledge Transfer and Domain Adaptation for Fine-Grained Remote Sensing Image Segmentation Cloudsen12, a global dataset for semantic understanding of cloud and cloud shadow in sentinel-2,

Reference 35

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This paper cites High-resolution cloud detection network,.

Knowledge Transfer and Domain Adaptation for Fine-Grained Remote Sensing Image Segmentation High-resolution cloud detection network,

Reference 36

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Observation e77dd5bd-8c4d-4e47-baa4-a5a634e9d90c · outbound

This paper cites Kappa- mask: Ai-based cloudmask processor for sentinel-2,.

Knowledge Transfer and Domain Adaptation for Fine-Grained Remote Sensing Image Segmentation Kappa- mask: Ai-based cloudmask processor for sentinel-2,

Reference 37

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Pith citing papers

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