Paper Citation Record · LEDGER

RemoteTrimmer: Adaptive Structural Pruning for Remote Sensing Image Classification

As of 23 August 2026, this Paper Citation Record lists 43 of 43 outbound references and 0 inbound Pith citation observations for arXiv:2412.12603.

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

pith.paper-citation-record.v1
2412.12603 v2

Coverage vector

measured 43 of 43 reference resolution

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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.

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

Source: cited_works

Reference resolution

43 of 43 outbound references displayed

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External citation measurements

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Outbound references

Observation 9694f802-8b3a-437c-870d-61379a23ba0f · outbound

This paper cites The national entiron- mental and geological information system for remote sensing survey and monitoring,.

RemoteTrimmer: Adaptive Structural Pruning for Remote Sensing Image Classification The national entiron- mental and geological information system for remote sensing survey and monitoring,

Reference 1

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Observation b8f69317-9e1f-40a9-8878-01549bc64593 · outbound

This paper cites Gross and net primary production in the global ocean: An ocean color remote sensing perspective,.

RemoteTrimmer: Adaptive Structural Pruning for Remote Sensing Image Classification Gross and net primary production in the global ocean: An ocean color remote sensing perspective,

Reference 2

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Observation d586542d-8bab-4544-8c2a-328e78e3d226 · outbound

This paper cites Remote sensing of soil degradation: Progress and perspective,.

RemoteTrimmer: Adaptive Structural Pruning for Remote Sensing Image Classification Remote sensing of soil degradation: Progress and perspective,

Reference 3

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Observation 50d7e9af-a140-4731-8971-d5b1f9af11b3 · outbound

This paper cites A survey of machine learning and deep learning in remote sensing of geological environment: Challenges, advances, and opportunities,.

RemoteTrimmer: Adaptive Structural Pruning for Remote Sensing Image Classification A survey of machine learning and deep learning in remote sensing of geological environment: Challenges, advances, and opportunities,

Reference 4

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Observation 46040f64-3bb7-4c7b-9daf-74d1e4f8a884 · outbound

This paper cites Geological survey of urban roadbeds utilizing rapid detection system based on transient electromagnetic method,.

RemoteTrimmer: Adaptive Structural Pruning for Remote Sensing Image Classification Geological survey of urban roadbeds utilizing rapid detection system based on transient electromagnetic method,

Reference 5

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Observation eda6a4dd-742a-4282-8538-59345bb416ff · outbound

This paper cites High-resolution remote sensing image scene understanding: A review,.

RemoteTrimmer: Adaptive Structural Pruning for Remote Sensing Image Classification High-resolution remote sensing image scene understanding: A review,

Reference 6

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Observation 1387b9d7-0717-4a4c-96ba-962c2a3dc9f4 · outbound

This paper cites Remote sensing image classification: A comprehensive review and applications,.

RemoteTrimmer: Adaptive Structural Pruning for Remote Sensing Image Classification Remote sensing image classification: A comprehensive review and applications,

Reference 7

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Observation 35de3f3b-ff38-40f3-a332-36eba5e07c14 · outbound

This paper cites A review of ensemble learning algo- rithms used in remote sensing applications,.

RemoteTrimmer: Adaptive Structural Pruning for Remote Sensing Image Classification A review of ensemble learning algo- rithms used in remote sensing applications,

Reference 8

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Observation c6703405-951e-4333-8666-31adc48e1614 · outbound

This paper cites Transfer learning in environmental remote sensing,.

RemoteTrimmer: Adaptive Structural Pruning for Remote Sensing Image Classification Transfer learning in environmental remote sensing,

Reference 9

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Observation 3eb48af4-ff20-44e7-9800-a1b379eaf549 · outbound

This paper cites Learning both weights and con- nections for efficient neural network,.

RemoteTrimmer: Adaptive Structural Pruning for Remote Sensing Image Classification Learning both weights and con- nections for efficient neural network,

Reference 10

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Observation f48ec504-8a1b-4a70-995d-caf5eaecbcd7 · outbound

This paper cites Distilling the Knowledge in a Neural Network.

RemoteTrimmer: Adaptive Structural Pruning for Remote Sensing Image Classification Distilling the Knowledge in a Neural Network

Reference 11

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Observation 44fcefe2-b384-4285-a41b-6ade0c3385b0 · outbound

This paper cites Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding.

RemoteTrimmer: Adaptive Structural Pruning for Remote Sensing Image Classification Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding

Reference 12

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Observation 0e6bffbd-cc8c-42bd-9204-008f8c318f10 · outbound

This paper cites Pruning filters for efficient convnets,.

RemoteTrimmer: Adaptive Structural Pruning for Remote Sensing Image Classification Pruning filters for efficient convnets,

Reference 13

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Observation 9a5ccd55-0df0-4981-b780-75ae72f0d0c6 · outbound

This paper cites Depgraph: Towards any structural pruning,.

RemoteTrimmer: Adaptive Structural Pruning for Remote Sensing Image Classification Depgraph: Towards any structural pruning,

Reference 14

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Observation 6c9e7336-3347-4ec6-be4d-65ca011dd354 · outbound

This paper cites Object detection in optical remote sensing images: A survey and a new benchmark,.

RemoteTrimmer: Adaptive Structural Pruning for Remote Sensing Image Classification Object detection in optical remote sensing images: A survey and a new benchmark,

Reference 15

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Observation 0bddc37f-97bb-4c06-979b-58ceedd8ec04 · outbound

This paper cites Convolutional neural networks for large-scale remote-sensing image classification,.

RemoteTrimmer: Adaptive Structural Pruning for Remote Sensing Image Classification Convolutional neural networks for large-scale remote-sensing image classification,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:00:39.498665Z

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Observation e3541bab-3766-479a-b2c2-a5f15161e1b0 · outbound

This paper cites A critical review of high and very high-resolution remote sensing approaches for detecting and mapping slums: Trends, challenges and emerging opportunities,.

RemoteTrimmer: Adaptive Structural Pruning for Remote Sensing Image Classification A critical review of high and very high-resolution remote sensing approaches for detecting and mapping slums: Trends, challenges and emerging opportunities,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:00:39.476835Z

Source-reported events for the cited work

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Observation 33f7c97f-7c7c-4d9f-932c-5b384e37d239 · outbound

This paper cites Improved remote sensing image classification based on multi- scale feature fusion,.

RemoteTrimmer: Adaptive Structural Pruning for Remote Sensing Image Classification Improved remote sensing image classification based on multi- scale feature fusion,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:00:39.457944Z

Source-reported events for the cited work

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Observation 14b3e215-6ef7-4c94-9d8b-d779973a040d · outbound

This paper cites Multi-scale dense networks for hyper- spectral remote sensing image classification,.

RemoteTrimmer: Adaptive Structural Pruning for Remote Sensing Image Classification Multi-scale dense networks for hyper- spectral remote sensing image classification,

Reference 19

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Observation 2ce9b212-3cb6-4aa0-b70a-5771647af038 · outbound

This paper cites Pruning convolutional neural networks with an attention mechanism for remote sensing image classi- fication,.

RemoteTrimmer: Adaptive Structural Pruning for Remote Sensing Image Classification Pruning convolutional neural networks with an attention mechanism for remote sensing image classi- fication,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:00:39.413241Z

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Observation 079c3d78-c1d5-4fbd-a347-626f0f5af4e6 · outbound

This paper cites Nas-based cnn channel pruning for remote sensing scene classification,.

RemoteTrimmer: Adaptive Structural Pruning for Remote Sensing Image Classification Nas-based cnn channel pruning for remote sensing scene classification,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:00:39.391427Z

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Observation c0a7ccf9-5616-44e2-98c8-94f80fd54821 · outbound

This paper cites Data customization-based multiobjective optimization pruning framework for remote sensing scene classification,.

RemoteTrimmer: Adaptive Structural Pruning for Remote Sensing Image Classification Data customization-based multiobjective optimization pruning framework for remote sensing scene classification,

Reference 22

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Observation 671a4017-a8c2-4368-9ec6-c01ccf4c12da · outbound

This paper cites A light-weight deep learning model for remote sensing image classification,.

RemoteTrimmer: Adaptive Structural Pruning for Remote Sensing Image Classification A light-weight deep learning model for remote sensing image classification,

Reference 23

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Observation e01c863e-cad5-4532-88bd-64f3427c1cd8 · outbound

This paper cites Rscnet: An efficient remote sensing scene classification model based on lightweight convolution neural networks,.

RemoteTrimmer: Adaptive Structural Pruning for Remote Sensing Image Classification Rscnet: An efficient remote sensing scene classification model based on lightweight convolution neural networks,

Reference 24

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Observation 2443420b-03f2-4bd3-9c86-36264ea98de3 · outbound

This paper cites Cloud and cloud shadow detection for optical satellite imagery: Features, al- gorithms, validation, and prospects,.

RemoteTrimmer: Adaptive Structural Pruning for Remote Sensing Image Classification Cloud and cloud shadow detection for optical satellite imagery: Features, al- gorithms, validation, and prospects,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:00:39.282603Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 9e6d865e-c9c7-4af1-8845-1dad3a147b22 · outbound

This paper cites Remote sensing image restoration using various techniques: A review,.

RemoteTrimmer: Adaptive Structural Pruning for Remote Sensing Image Classification Remote sensing image restoration using various techniques: A review,

Reference 26

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Observation 781f03b9-0870-4774-9dd2-57ba28acec44 · outbound

This paper cites Atmospheric correction algorithms for hyperspectral remote sensing data of land and ocean,.

RemoteTrimmer: Adaptive Structural Pruning for Remote Sensing Image Classification Atmospheric correction algorithms for hyperspectral remote sensing data of land and ocean,

Reference 27

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Observation 0f662eb9-e324-4954-9023-c094d011812c · outbound

This paper cites Comprehensive investigation of the atmospheric modulation transfer function (mtf) for satellite imaging pay- loads: considering turbulence and aerosol effects over tehran,.

RemoteTrimmer: Adaptive Structural Pruning for Remote Sensing Image Classification Comprehensive investigation of the atmospheric modulation transfer function (mtf) for satellite imaging pay- loads: considering turbulence and aerosol effects over tehran,

Reference 28

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Observation a5d076c6-c652-459b-a5f7-c412e8a859b8 · outbound

This paper cites Visual attention methods in deep learning: An in-depth survey,.

RemoteTrimmer: Adaptive Structural Pruning for Remote Sensing Image Classification Visual attention methods in deep learning: An in-depth survey,

Reference 29

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Observation 128c5cd0-7055-43b0-b65d-3942d23eed3f · outbound

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RemoteTrimmer: Adaptive Structural Pruning for Remote Sensing Image Classification Squeeze-and-excitation networks,

Reference 30

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This paper cites Deep residual learning for image recognition,.

RemoteTrimmer: Adaptive Structural Pruning for Remote Sensing Image Classification Deep residual learning for image recognition,

Reference 31

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This paper cites Deep sparse rectifier neural networks,.

RemoteTrimmer: Adaptive Structural Pruning for Remote Sensing Image Classification Deep sparse rectifier neural networks,

Reference 32

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Observation 04cf5d2a-63f8-4833-9855-bcffcc8cf89c · outbound

This paper cites Learning efficient convolutional networks through network slimming,.

RemoteTrimmer: Adaptive Structural Pruning for Remote Sensing Image Classification Learning efficient convolutional networks through network slimming,

Reference 33

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Observation 63ff0fb1-f4f8-46da-80ce-8ea3e45acbfa · outbound

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RemoteTrimmer: Adaptive Structural Pruning for Remote Sensing Image Classification Pruning Filters for Efficient ConvNets

Reference 34

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Observation 9726b85d-8e80-41c9-b3d5-1fba723e08b6 · outbound

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RemoteTrimmer: Adaptive Structural Pruning for Remote Sensing Image Classification Filter pruning via geometric median for deep convolutional neural networks acceleration,

Reference 35

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RemoteTrimmer: Adaptive Structural Pruning for Remote Sensing Image Classification Focal loss for dense object detection,

Reference 36

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Observation 0e248978-2d16-4820-b1fe-6dbd1c576400 · outbound

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

RemoteTrimmer: Adaptive Structural Pruning for Remote Sensing Image Classification Eurosat: A novel dataset and deep learning benchmark for land use and land cover classi- fication,

Reference 37

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Observation ca0c185d-7bc8-4609-8b70-85ca9613594d · outbound

This paper cites Deep semantic understanding of high resolution remote sensing image,.

RemoteTrimmer: Adaptive Structural Pruning for Remote Sensing Image Classification Deep semantic understanding of high resolution remote sensing image,

Reference 38

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Source-reported events for the cited work

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Observation 74efb9ed-97cf-466c-a0c1-6eedbb255843 · outbound

This paper cites Towards performance-maximizing neural network pruning via global channel attention,.

RemoteTrimmer: Adaptive Structural Pruning for Remote Sensing Image Classification Towards performance-maximizing neural network pruning via global channel attention,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:00:39.023172Z

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Observation 20a16eaa-ff48-48f8-8c32-6ec31920f48f · outbound

This paper cites Very Deep Convolutional Networks for Large-Scale Image Recognition.

RemoteTrimmer: Adaptive Structural Pruning for Remote Sensing Image Classification Very Deep Convolutional Networks for Large-Scale Image Recognition

Reference 40

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Observation bc40ae24-7d07-4078-a707-14342b25e5e6 · outbound

This paper cites Sgd: Saccharomyces genome database,.

RemoteTrimmer: Adaptive Structural Pruning for Remote Sensing Image Classification Sgd: Saccharomyces genome database,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:00:38.993467Z

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Observation 78b7df27-7588-47b5-b487-0f61f99d2ee8 · outbound

This paper cites Cbam: Convolutional block attention module,.

RemoteTrimmer: Adaptive Structural Pruning for Remote Sensing Image Classification Cbam: Convolutional block attention module,

Reference 42

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Observation ec5dd6a2-909e-4d68-9e22-7681493b7157 · outbound

This paper cites BAM: Bottleneck Attention Module.

RemoteTrimmer: Adaptive Structural Pruning for Remote Sensing Image Classification BAM: Bottleneck Attention Module

Reference 43

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