Paper Citation Record · LEDGER

Revealing the Ancient Beauty: Digital Reconstruction of Temple Tiles using Computer Vision

As of 8 August 2026, this Paper Citation Record lists 42 of 42 outbound references and 0 inbound Pith citation observations for arXiv:2507.12195.

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

pith.paper-citation-record.v1
2507.12195 v1

Coverage vector

measured 42 of 42 reference resolution

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One-hop event checks from named stored sources.

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Pith citing papers itemized under the disclosed page cap.

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Source: cited_works

Reference resolution

42 of 42 outbound references displayed

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External citation measurements

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Outbound references

Observation 8da62565-63bc-4e39-88e5-4525dfbb1777 · outbound

This paper cites Digital restoration of cultural heritage with data-driven computing: A sur- vey,.

Revealing the Ancient Beauty: Digital Reconstruction of Temple Tiles using Computer Vision Digital restoration of cultural heritage with data-driven computing: A sur- vey,

Reference 1

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This paper cites The influence of traditional indian architecture in balkrishna doshi’s iim complex at bangalore: A comparative analysis using fractal dimensions and lacunarity,.

Revealing the Ancient Beauty: Digital Reconstruction of Temple Tiles using Computer Vision The influence of traditional indian architecture in balkrishna doshi’s iim complex at bangalore: A comparative analysis using fractal dimensions and lacunarity,

Reference 2

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Revealing the Ancient Beauty: Digital Reconstruction of Temple Tiles using Computer Vision Fast box-counting algorithm on gpu,

Reference 3

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This paper cites How long is the coast of britain? statistical self-similarity and fractional dimension,.

Revealing the Ancient Beauty: Digital Reconstruction of Temple Tiles using Computer Vision How long is the coast of britain? statistical self-similarity and fractional dimension,

Reference 4

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Revealing the Ancient Beauty: Digital Reconstruction of Temple Tiles using Computer Vision Unresolved cited work

Reference 5

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Observation 739e9ef0-de3f-4124-a075-2e0354a682f8 · outbound

This paper cites Fractal dimension calculation and visual attention simulation: Assessing the visual character of an architectural fa¸ cade,.

Revealing the Ancient Beauty: Digital Reconstruction of Temple Tiles using Computer Vision Fractal dimension calculation and visual attention simulation: Assessing the visual character of an architectural fa¸ cade,

Reference 6

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This paper cites Fractal analysis applied to ancient egyptian monumental art,.

Revealing the Ancient Beauty: Digital Reconstruction of Temple Tiles using Computer Vision Fractal analysis applied to ancient egyptian monumental art,

Reference 7

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This paper cites A method of compositional fractal analy- sis and its application in islamic architectural ensembles,.

Revealing the Ancient Beauty: Digital Reconstruction of Temple Tiles using Computer Vision A method of compositional fractal analy- sis and its application in islamic architectural ensembles,

Reference 8

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This paper cites A three-dimensional box-counting method to study the fractal characteristics of urban areas in shenyang, northeast china,.

Revealing the Ancient Beauty: Digital Reconstruction of Temple Tiles using Computer Vision A three-dimensional box-counting method to study the fractal characteristics of urban areas in shenyang, northeast china,

Reference 9

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Observation 65eb7c4a-6ae5-4e29-b4b0-07dd0440bcec · outbound

This paper cites Indonesia ancient temple clas- sification using convolutional neural network,.

Revealing the Ancient Beauty: Digital Reconstruction of Temple Tiles using Computer Vision Indonesia ancient temple clas- sification using convolutional neural network,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:58:40.196416Z

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This paper cites Classification of architectural heritage images using deep learning techniques,.

Revealing the Ancient Beauty: Digital Reconstruction of Temple Tiles using Computer Vision Classification of architectural heritage images using deep learning techniques,

Reference 11

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Revealing the Ancient Beauty: Digital Reconstruction of Temple Tiles using Computer Vision Generative adversarial networks,

Reference 12

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This paper cites Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks.

Revealing the Ancient Beauty: Digital Reconstruction of Temple Tiles using Computer Vision Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks

Reference 13

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This paper cites Esrgan: Enhanced super-resolution generative adversarial networks,.

Revealing the Ancient Beauty: Digital Reconstruction of Temple Tiles using Computer Vision Esrgan: Enhanced super-resolution generative adversarial networks,

Reference 15

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This paper cites You only look once: Unified, real-time object detection,.

Revealing the Ancient Beauty: Digital Reconstruction of Temple Tiles using Computer Vision You only look once: Unified, real-time object detection,

Reference 16

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Observation 87cc6be9-22d0-49fa-8bc0-069fae90b301 · outbound

This paper cites YOLOv3: An Incremental Improvement.

Revealing the Ancient Beauty: Digital Reconstruction of Temple Tiles using Computer Vision YOLOv3: An Incremental Improvement

Reference 17

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Revealing the Ancient Beauty: Digital Reconstruction of Temple Tiles using Computer Vision Yolov4: Optimal speed and accuracy of object detection,

Reference 18

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Revealing the Ancient Beauty: Digital Reconstruction of Temple Tiles using Computer Vision Ssd lite: A lightweight single shot multibox detector,

Reference 19

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Revealing the Ancient Beauty: Digital Reconstruction of Temple Tiles using Computer Vision Ssd: Single shot multibox detector,

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Revealing the Ancient Beauty: Digital Reconstruction of Temple Tiles using Computer Vision Attention Is All You Need

Reference 21

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Revealing the Ancient Beauty: Digital Reconstruction of Temple Tiles using Computer Vision You only look once: Unified, real-time object detection,

Reference 22

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Revealing the Ancient Beauty: Digital Reconstruction of Temple Tiles using Computer Vision Yolo9000: Better, faster, stronger,

Reference 23

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Revealing the Ancient Beauty: Digital Reconstruction of Temple Tiles using Computer Vision Yolov3: An incremental improvement,

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Revealing the Ancient Beauty: Digital Reconstruction of Temple Tiles using Computer Vision Ultra Fast Object Detection in YOLOv5,

Reference 25

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Revealing the Ancient Beauty: Digital Reconstruction of Temple Tiles using Computer Vision YOLOv8: The Evolution of Object Detection,

Reference 26

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Revealing the Ancient Beauty: Digital Reconstruction of Temple Tiles using Computer Vision Covariant holographic entanglement negativity

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Revealing the Ancient Beauty: Digital Reconstruction of Temple Tiles using Computer Vision MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications

Reference 28

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Revealing the Ancient Beauty: Digital Reconstruction of Temple Tiles using Computer Vision Charge Transfer Database for Bio-molecule Tight Binding Model Derived from Thousands of Proteins

Reference 29

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Revealing the Ancient Beauty: Digital Reconstruction of Temple Tiles using Computer Vision Image super-resolution using deep convolutional networks,

Reference 30

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Revealing the Ancient Beauty: Digital Reconstruction of Temple Tiles using Computer Vision Deep back-projectinetworks for single image super-resolution,

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Revealing the Ancient Beauty: Digital Reconstruction of Temple Tiles using Computer Vision Single image super-resolution from transformed self-exemplars,

Reference 32

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Revealing the Ancient Beauty: Digital Reconstruction of Temple Tiles using Computer Vision Esrgan+: Further improving en- hanced super-resolution generative adversarial network,

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Revealing the Ancient Beauty: Digital Reconstruction of Temple Tiles using Computer Vision Second-order attention network for magnification-arbitrary single image super-resolution,

Reference 34

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Revealing the Ancient Beauty: Digital Reconstruction of Temple Tiles using Computer Vision Swinir: Image restoration using swin transformer,

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Revealing the Ancient Beauty: Digital Reconstruction of Temple Tiles using Computer Vision SwinFIR: Revisiting the SwinIR with Fast Fourier Convolution and Improved Training for Image Super-Resolution

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Revealing the Ancient Beauty: Digital Reconstruction of Temple Tiles using Computer Vision A computational approach to edge detection,

Reference 37

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This paper cites Design of an image edge de- tection filter using the sobel operator,.

Revealing the Ancient Beauty: Digital Reconstruction of Temple Tiles using Computer Vision Design of an image edge de- tection filter using the sobel operator,

Reference 38

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This paper cites A three dimensional box counting method for measuring fractal dimensions of 3d models,.

Revealing the Ancient Beauty: Digital Reconstruction of Temple Tiles using Computer Vision A three dimensional box counting method for measuring fractal dimensions of 3d models,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:58:36.290546Z

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This paper cites On regenerative and discriminative learning from digital heritages: A fractal dimension based ap- proach,.

Revealing the Ancient Beauty: Digital Reconstruction of Temple Tiles using Computer Vision On regenerative and discriminative learning from digital heritages: A fractal dimension based ap- proach,

Reference 40

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This paper cites Progressive Growing of GANs for Improved Quality, Stability, and Variation.

Revealing the Ancient Beauty: Digital Reconstruction of Temple Tiles using Computer Vision Progressive Growing of GANs for Improved Quality, Stability, and Variation

Reference 41

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This paper cites Photo-realistic single image super-resolution using a generative adversarial network,.

Revealing the Ancient Beauty: Digital Reconstruction of Temple Tiles using Computer Vision Photo-realistic single image super-resolution using a generative adversarial network,

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This paper cites Available: http://www.sciencemag.org/content/156/3775/ 636.abstract.

Revealing the Ancient Beauty: Digital Reconstruction of Temple Tiles using Computer Vision Available: http://www.sciencemag.org/content/156/3775/ 636.abstract

Reference 1967

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Pith citing papers

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