Enhancing Content Representation for AR Image Quality Assessment Using Knowledge Distillation | Paper Citation Record

Observation 40603010-2bb4-4fc8-b41b-4ae274353f19 · outbound

This paper cites Head-worn displays: a review,.

Enhancing Content Representation for AR Image Quality Assessment Using Knowledge Distillation Head-worn displays: a review,

Reference 1

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Observation 99b8998e-77c0-46a0-8b08-e3d4f67fc717 · outbound

This paper cites Augmented reality and virtual reality displays: perspectives and challenges,.

Enhancing Content Representation for AR Image Quality Assessment Using Knowledge Distillation Augmented reality and virtual reality displays: perspectives and challenges,

Reference 2

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Observation df1eb042-535e-4329-a0b3-be69757c20f4 · outbound

This paper cites History of augmented reality,.

Enhancing Content Representation for AR Image Quality Assessment Using Knowledge Distillation History of augmented reality,

Reference 3

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Observation 1a7f92ec-1e73-478d-bcf7-3c3f02f466cd · outbound

This paper cites Deep-based quality assessment of medical images through domain adaptation,.

Enhancing Content Representation for AR Image Quality Assessment Using Knowledge Distillation Deep-based quality assessment of medical images through domain adaptation,

Reference 4

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Observation 48191757-6228-4cd2-bdf4-cb87fe0747c8 · outbound

This paper cites International Telecommu- nication Union.

Enhancing Content Representation for AR Image Quality Assessment Using Knowledge Distillation International Telecommu- nication Union

Reference 5

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Observation 61708051-3a13-4e6e-9b1a-e3993ecc2f00 · outbound

This paper cites QUALINET White Paper on Definitions of Immersive Media Experience (IMEx).

Enhancing Content Representation for AR Image Quality Assessment Using Knowledge Distillation QUALINET White Paper on Definitions of Immersive Media Experience (IMEx)

Reference 6

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Enhancing Content Representation for AR Image Quality Assessment Using Knowledge Distillation Unresolved cited work

Reference 7

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This paper cites Research and application of the adaptive model of the human visual sys- tem for improving the effectiveness of objective video quality metrics,.

Enhancing Content Representation for AR Image Quality Assessment Using Knowledge Distillation Research and application of the adaptive model of the human visual sys- tem for improving the effectiveness of objective video quality metrics,

Reference 8

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Observation b84864ef-8bea-4399-8110-4c90566a7096 · outbound

This paper cites Dashrestreamer: Framework for creation of impaired video clips under realistic network conditions,.

Enhancing Content Representation for AR Image Quality Assessment Using Knowledge Distillation Dashrestreamer: Framework for creation of impaired video clips under realistic network conditions,

Reference 9

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Observation 5e8b99d2-f58b-4e24-a0f9-a0f1eebaa8ba · outbound

This paper cites Iv- psnr—the objective quality metric for immersive video applications,.

Enhancing Content Representation for AR Image Quality Assessment Using Knowledge Distillation Iv- psnr—the objective quality metric for immersive video applications,

Reference 10

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Observation abc38aa8-c6ff-44f9-ae5f-ec9355aea455 · outbound

This paper cites A bayesian quality-of-experience model for adaptive streaming videos,.

Enhancing Content Representation for AR Image Quality Assessment Using Knowledge Distillation A bayesian quality-of-experience model for adaptive streaming videos,

Reference 11

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Observation 7b3f3f6a-14f3-4d61-97fc-6a91adf5004a · outbound

This paper cites Itu-t recommendation g.1036,.

Enhancing Content Representation for AR Image Quality Assessment Using Knowledge Distillation Itu-t recommendation g.1036,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:10:32.327057Z

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Observation 1c93e4e6-5129-4a1b-b7ad-79c0b6cada7e · outbound

This paper cites Objective and subjective quality assessment of 360- degree images,.

Enhancing Content Representation for AR Image Quality Assessment Using Knowledge Distillation Objective and subjective quality assessment of 360- degree images,

Reference 13

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Observation df8f00bf-42fa-40a4-92ca-766d3fd39033 · outbound

This paper cites Attentive deep image quality assessment for omnidirectional stitching,.

Enhancing Content Representation for AR Image Quality Assessment Using Knowledge Distillation Attentive deep image quality assessment for omnidirectional stitching,

Reference 14

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Observation 221a0b3e-8adc-4dea-8f7b-62dcdebe7267 · outbound

This paper cites Perceptual Quality Assessment of Omnidirectional Audio-visual Signals.

Enhancing Content Representation for AR Image Quality Assessment Using Knowledge Distillation Perceptual Quality Assessment of Omnidirectional Audio-visual Signals

Reference 15

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Observation 351e2c43-27d4-411b-87ef-53c5a5ec6b52 · outbound

This paper cites Acr360: A dataset on subjective 360° video quality assessment using acr methods,.

Enhancing Content Representation for AR Image Quality Assessment Using Knowledge Distillation Acr360: A dataset on subjective 360° video quality assessment using acr methods,

Reference 16

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Observation e6748346-cb9d-46de-9edb-a2c7b2079483 · outbound

This paper cites Subjective quality assessment of stereoscopic omnidirectional image,.

Enhancing Content Representation for AR Image Quality Assessment Using Knowledge Distillation Subjective quality assessment of stereoscopic omnidirectional image,

Reference 17

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Observation 10ca084b-2d21-4411-9087-e529205c16aa · outbound

This paper cites Study of 3D virtual reality picture quality,.

Enhancing Content Representation for AR Image Quality Assessment Using Knowledge Distillation Study of 3D virtual reality picture quality,

Reference 18

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Observation 26824d5f-04e3-4397-b625-e637bbb535ff · outbound

This paper cites 3d22 mx: Performance subjective evalu- ation of 3D/stereoscopic image processing and analysis,.

Enhancing Content Representation for AR Image Quality Assessment Using Knowledge Distillation 3d22 mx: Performance subjective evalu- ation of 3D/stereoscopic image processing and analysis,

Reference 19

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Observation 3578f277-59d2-4928-a1c3-90a9332b6a5f · outbound

This paper cites Subjective quality database and objective study of compressed point clouds with 6dof head- mounted display,.

Enhancing Content Representation for AR Image Quality Assessment Using Knowledge Distillation Subjective quality database and objective study of compressed point clouds with 6dof head- mounted display,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:10:32.242957Z

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Observation e289eaf0-0627-4f23-bebd-fea0b55ccca3 · outbound

This paper cites Subjective and objective visual quality assessment of textured 3D meshes,.

Enhancing Content Representation for AR Image Quality Assessment Using Knowledge Distillation Subjective and objective visual quality assessment of textured 3D meshes,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:10:32.229949Z

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Observation cce0e522-98d5-4dd4-b979-90acf23629e7 · outbound

This paper cites Quality evaluation of 3D objects in mixed reality for different lighting conditions,.

Enhancing Content Representation for AR Image Quality Assessment Using Knowledge Distillation Quality evaluation of 3D objects in mixed reality for different lighting conditions,

Reference 22

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Observation 61714ae5-1b16-4f31-a41b-78e7de5bad97 · outbound

This paper cites Towards subjective quality assessment of point cloud imaging in augmented reality,.

Enhancing Content Representation for AR Image Quality Assessment Using Knowledge Distillation Towards subjective quality assessment of point cloud imaging in augmented reality,

Reference 23

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Observation fd128616-68c3-4e6d-bba2-78e778fa4803 · outbound

This paper cites Confusing image quality assessment: Toward better augmented reality experience,.

Enhancing Content Representation for AR Image Quality Assessment Using Knowledge Distillation Confusing image quality assessment: Toward better augmented reality experience,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:10:32.192072Z

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Observation 05600ea8-55c3-4906-88e1-22ac7354de47 · outbound

This paper cites Image quality assess- ment: from error visibility to structural similarity,.

Enhancing Content Representation for AR Image Quality Assessment Using Knowledge Distillation Image quality assess- ment: from error visibility to structural similarity,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:10:32.181073Z

Source-reported events for the cited work

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Observation 5f33acab-f416-488c-b388-73c846dab25e · outbound

This paper cites Multiscale structural similarity for image quality assessment,.

Enhancing Content Representation for AR Image Quality Assessment Using Knowledge Distillation Multiscale structural similarity for image quality assessment,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:10:32.168058Z

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Observation 053d6204-24f6-49df-9323-d5546bc2bc94 · outbound

This paper cites Information content weighting for perceptual image quality assessment,.

Enhancing Content Representation for AR Image Quality Assessment Using Knowledge Distillation Information content weighting for perceptual image quality assessment,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:10:32.155707Z

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Observation 14953056-0559-4174-a939-f271594d086c · outbound

This paper cites Fsim: A feature similarity index for image quality assessment,.

Enhancing Content Representation for AR Image Quality Assessment Using Knowledge Distillation Fsim: A feature similarity index for image quality assessment,

Reference 28

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Observation 7e9c2af0-a48e-4c6f-b1c4-0e5222b60d14 · outbound

This paper cites Simultaneous estimation of image quality and distortion via multi-task convolutional neural networks,.

Enhancing Content Representation for AR Image Quality Assessment Using Knowledge Distillation Simultaneous estimation of image quality and distortion via multi-task convolutional neural networks,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:10:32.136183Z

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Observation 2bd26e50-948b-4aeb-a7d2-3ab8232cb60d · outbound

This paper cites Image quality assessment: a sparse learning way,.

Enhancing Content Representation for AR Image Quality Assessment Using Knowledge Distillation Image quality assessment: a sparse learning way,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:10:32.123353Z

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Observation 77d9a753-41af-40f2-8b20-c307ef27b3f1 · outbound

This paper cites Deep neural networks for no- reference and full-reference image quality assessment,.

Enhancing Content Representation for AR Image Quality Assessment Using Knowledge Distillation Deep neural networks for no- reference and full-reference image quality assessment,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:10:32.111323Z

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Observation 3f49e973-b237-4d42-8e37-f4c74c9b7ad6 · outbound

This paper cites The unreasonable effectiveness of deep features as a perceptual metric,.

Enhancing Content Representation for AR Image Quality Assessment Using Knowledge Distillation The unreasonable effectiveness of deep features as a perceptual metric,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:10:32.098092Z

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Observation 5b07bd4b-a746-47d4-bf0a-0b72607175d2 · outbound

This paper cites Squeezenet: Alexnet-level accuracy with 50x fewer param- eters and ¡ 0.5 mb model size,.

Enhancing Content Representation for AR Image Quality Assessment Using Knowledge Distillation Squeezenet: Alexnet-level accuracy with 50x fewer param- eters and ¡ 0.5 mb model size,

Reference 33

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Observation f6aebd99-9456-4f39-aa13-34bf32ad1952 · outbound

This paper cites Imagenet classification with deep convolutional neural networks,.

Enhancing Content Representation for AR Image Quality Assessment Using Knowledge Distillation Imagenet classification with deep convolutional neural networks,

Reference 34

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Observation 5cac6acd-1053-4bf4-8c75-ba3e2c4e99fb · outbound

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

Enhancing Content Representation for AR Image Quality Assessment Using Knowledge Distillation Very Deep Convolutional Networks for Large-Scale Image Recognition

Reference 35

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Observation a56c4239-bd2d-4831-8938-4c9e3a96e946 · outbound

This paper cites Perceptual image quality assessment with transformers,.

Enhancing Content Representation for AR Image Quality Assessment Using Knowledge Distillation Perceptual image quality assessment with transformers,

Reference 36

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Observation 26c15e52-e411-465b-8a8a-6de569fbebdf · outbound

This paper cites No-reference image qual- ity assessment via transformers, relative ranking, and self-consistency,.

Enhancing Content Representation for AR Image Quality Assessment Using Knowledge Distillation No-reference image qual- ity assessment via transformers, relative ranking, and self-consistency,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:10:32.047957Z

Source-reported events for the cited work

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Observation 92aea6cb-73a7-4c19-9caf-beb70032aacf · outbound

This paper cites Image quality assessment with transformers and multi-metric fusion modules,.

Enhancing Content Representation for AR Image Quality Assessment Using Knowledge Distillation Image quality assessment with transformers and multi-metric fusion modules,

Reference 38

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Observation ef4ae526-d435-4b0f-9b25-081efac647f5 · outbound

This paper cites Perceptual video coding based on ssim-inspired divisive normalization,.

Enhancing Content Representation for AR Image Quality Assessment Using Knowledge Distillation Perceptual video coding based on ssim-inspired divisive normalization,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:10:32.021423Z

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Observation 0ea8b9a0-b37e-4057-b30f-60cb2dd8cbd2 · outbound

This paper cites Perceptual quality assessment for multi-exposure image fusion,.

Enhancing Content Representation for AR Image Quality Assessment Using Knowledge Distillation Perceptual quality assessment for multi-exposure image fusion,

Reference 40

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Observation 439ff66b-37b3-4931-be0c-297934809ecd · outbound

This paper cites Automatic contrast enhancement technology with saliency preservation,.

Enhancing Content Representation for AR Image Quality Assessment Using Knowledge Distillation Automatic contrast enhancement technology with saliency preservation,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:10:31.998494Z

Source-reported events for the cited work

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Observation 4d13a392-403a-401d-aa50-8baa5a0722de · outbound

This paper cites Image quality assessment based on a degradation model,.

Enhancing Content Representation for AR Image Quality Assessment Using Knowledge Distillation Image quality assessment based on a degradation model,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:10:31.986145Z

Source-reported events for the cited work

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Observation 8fdf3022-23b4-4c84-9e8d-ecf9d013cf38 · outbound

This paper cites Image information and visual quality,.

Enhancing Content Representation for AR Image Quality Assessment Using Knowledge Distillation Image information and visual quality,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:10:31.973472Z

Source-reported events for the cited work

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Observation 953a3cbd-088b-4816-81c7-428a51c1a2be · outbound

This paper cites Image quality assessment based on gradient similarity,.

Enhancing Content Representation for AR Image Quality Assessment Using Knowledge Distillation Image quality assessment based on gradient similarity,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:10:31.960747Z

Source-reported events for the cited work

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Observation 238de8da-02d7-495a-b812-92231f67a2b2 · outbound

This paper cites Gradient magnitude similarity deviation: A highly efficient perceptual image quality index,.

Enhancing Content Representation for AR Image Quality Assessment Using Knowledge Distillation Gradient magnitude similarity deviation: A highly efficient perceptual image quality index,

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:10:31.948947Z

Source-reported events for the cited work

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Observation 746ab756-ecce-4d10-850e-b62b9a79e471 · outbound

This paper cites Perceptual fidelity aware mean squared error,.

Enhancing Content Representation for AR Image Quality Assessment Using Knowledge Distillation Perceptual fidelity aware mean squared error,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:10:31.937054Z

Source-reported events for the cited work

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Observation 13f0cdbe-a2bc-4e26-a7b9-63135b6ef178 · outbound

This paper cites An efficient color image quality metric with local-tuned-global model,.

Enhancing Content Representation for AR Image Quality Assessment Using Knowledge Distillation An efficient color image quality metric with local-tuned-global model,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:10:31.924633Z

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 78adf6dc-5d31-4118-b13e-6f7e11df36d3 · outbound

This paper cites Vsi: A visual saliency-induced index for perceptual image quality assessment,.

Enhancing Content Representation for AR Image Quality Assessment Using Knowledge Distillation Vsi: A visual saliency-induced index for perceptual image quality assessment,

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-11T20:10:31.458553Z

Source-reported events for the cited work

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Observation 7c50949e-1928-4206-9a70-a33a1f4168ab · outbound

This paper cites Deep residual learning for image recognition,.

Enhancing Content Representation for AR Image Quality Assessment Using Knowledge Distillation Deep residual learning for image recognition,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:10:31.904131Z

Source-reported events for the cited work

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Observation 0ac15241-6010-4095-b433-0b38db6e2929 · outbound

This paper cites Influence of affective image content on subjective quality assessment,.

Enhancing Content Representation for AR Image Quality Assessment Using Knowledge Distillation Influence of affective image content on subjective quality assessment,

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:10:31.892114Z

Source-reported events for the cited work

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Observation a51df8fd-d8f0-4634-8276-948e62ae5b96 · outbound

This paper cites Do vision transformers see like convolutional neural networks?.

Enhancing Content Representation for AR Image Quality Assessment Using Knowledge Distillation Do vision transformers see like convolutional neural networks?

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:10:31.879206Z

Source-reported events for the cited work

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Observation 62e27590-96be-4186-9947-e7ac49267087 · outbound

This paper cites UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction.

Enhancing Content Representation for AR Image Quality Assessment Using Knowledge Distillation UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-11T20:10:31.473868Z

Source-reported events for the cited work

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Observation 2c3dc101-7af2-4447-9afa-0181fbe8b9ce · outbound

This paper cites Attention is all you need,.

Enhancing Content Representation for AR Image Quality Assessment Using Knowledge Distillation Attention is all you need,

Reference 53

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This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

Enhancing Content Representation for AR Image Quality Assessment Using Knowledge Distillation An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 54

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This paper cites To Compress or Not to Compress- Self-Supervised Learning and Information Theory: A Review.

Enhancing Content Representation for AR Image Quality Assessment Using Knowledge Distillation To Compress or Not to Compress- Self-Supervised Learning and Information Theory: A Review

Reference 55

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This paper cites A Cookbook of Self-Supervised Learning.

Enhancing Content Representation for AR Image Quality Assessment Using Knowledge Distillation A Cookbook of Self-Supervised Learning

Reference 56

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This paper cites A simple framework for contrastive learning of visual representations,.

Enhancing Content Representation for AR Image Quality Assessment Using Knowledge Distillation A simple framework for contrastive learning of visual representations,

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:10:31.858563Z

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This paper cites Emerging properties in self-supervised vision transformers,.

Enhancing Content Representation for AR Image Quality Assessment Using Knowledge Distillation Emerging properties in self-supervised vision transformers,

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:10:31.846940Z

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This paper cites Barlow twins: Self- supervised learning via redundancy reduction,.

Enhancing Content Representation for AR Image Quality Assessment Using Knowledge Distillation Barlow twins: Self- supervised learning via redundancy reduction,

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:10:31.833854Z

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This paper cites VICReg: Variance-Invariance-Covariance Regularization for Self-Supervised Learning.

Enhancing Content Representation for AR Image Quality Assessment Using Knowledge Distillation VICReg: Variance-Invariance-Covariance Regularization for Self-Supervised Learning

Reference 60

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Enhancing Content Representation for AR Image Quality Assessment Using Knowledge Distillation Exploring simple siamese representation learning,

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:10:31.820451Z

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This paper cites Regularization and variable selection via the elastic net,.

Enhancing Content Representation for AR Image Quality Assessment Using Knowledge Distillation Regularization and variable selection via the elastic net,

Reference 62

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This paper cites Robust estimation of a location parameter,.

Enhancing Content Representation for AR Image Quality Assessment Using Knowledge Distillation Robust estimation of a location parameter,

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:10:31.797167Z

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This paper cites Decoupled Weight Decay Regularization.

Enhancing Content Representation for AR Image Quality Assessment Using Knowledge Distillation Decoupled Weight Decay Regularization

Reference 64

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Enhancing Content Representation for AR Image Quality Assessment Using Knowledge Distillation Mean deviation similarity index: Efficient and reliable full-reference image quality evaluator,

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:10:31.783368Z

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Observation aa6aa0e2-d6cb-4e29-93f2-bae86cb55014 · outbound

This paper cites Image quality assessment based on dct subband similarity,.

Enhancing Content Representation for AR Image Quality Assessment Using Knowledge Distillation Image quality assessment based on dct subband similarity,

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:10:31.768952Z

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This paper cites A Haar wavelet-based perceptual similarity index for image quality assessment,.

Enhancing Content Representation for AR Image Quality Assessment Using Knowledge Distillation A Haar wavelet-based perceptual similarity index for image quality assessment,

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:10:31.756405Z

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This paper cites Sr-sim: A fast and high performance iqa index based on spectral residual,.

Enhancing Content Representation for AR Image Quality Assessment Using Knowledge Distillation Sr-sim: A fast and high performance iqa index based on spectral residual,

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:10:31.742880Z

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This paper cites Towards light-weight transformer-based quality assessment metric for augmented reality,.

Enhancing Content Representation for AR Image Quality Assessment Using Knowledge Distillation Towards light-weight transformer-based quality assessment metric for augmented reality,

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:10:31.729637Z

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This paper cites Libsvm: a library for support vector machines,.

Enhancing Content Representation for AR Image Quality Assessment Using Knowledge Distillation Libsvm: a library for support vector machines,

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:10:31.717845Z

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This paper cites PyTorch Image Quality: Metrics for Image Quality Assessment.

Enhancing Content Representation for AR Image Quality Assessment Using Knowledge Distillation PyTorch Image Quality: Metrics for Image Quality Assessment

Reference 71

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