On the public citation graph

How to Tell Ancient Signs Apart? Recognizing and Visualizing Maya Glyphs with CNNs

https://doi.org/10.1145/3230670
0 signed · 52 inferred · view as graph

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

Is this your work? Sign in with ORCID and put your name on the claims that are yours.
Claim with ORCID
Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.
See reference health

What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/978-3-319-10590-1_53openalex-snapshot
Visualizing and Understanding Convolutional Networks
inferredcites →https://doi.org/10.1007/978-3-319-16178-5_9openalex-snapshot
Graph-Based Shape Similarity of Petroglyphs
inferredcites →https://doi.org/10.1007/978-3-319-46604-0_58openalex-snapshot
Transferring Neural Representations for Low-Dimensional Indexing of Maya Hieroglyphic Art
inferredcites →https://doi.org/10.1007/s10618-010-0200-zopenalex-snapshot
An efficient and effective similarity measure to enable data mining of petroglyphs
inferredcites →https://doi.org/10.1007/s11263-010-0387-xopenalex-snapshot
Analyzing Ancient Maya Glyph Collections with Contextual Shape Descriptors
inferredcites →https://doi.org/10.1016/j.daach.2015.03.001openalex-snapshot
Automated classification of petroglyphs
inferredcites →https://doi.org/10.1038/nature14539openalex-snapshot
Deep learning
inferredcites →https://doi.org/10.1080/01621459.1951.10500769openalex-snapshot
The Kolmogorov-Smirnov Test for Goodness of Fit
inferredcites →https://doi.org/10.1086/300142openalex-snapshot
The Language of Classic Maya Inscriptions
inferredcites →https://doi.org/10.1109/5.726791openalex-snapshot
Gradient-based learning applied to document recognition
inferredcites →https://doi.org/10.1109/cvpr.2009.5206848openalex-snapshot
ImageNet: A large-scale hierarchical image database
inferredcites →https://doi.org/10.1109/cvpr.2015.7298594openalex-snapshot
Going deeper with convolutions
inferredcites →https://doi.org/10.1109/cvpr.2016.319openalex-snapshot
Learning Deep Features for Discriminative Localization
inferredcites →https://doi.org/10.1109/cvpr.2016.90openalex-snapshot
Deep Residual Learning for Image Recognition
inferredcites →https://doi.org/10.1109/cvprw.2014.131openalex-snapshot
CNN Features Off-the-Shelf: An Astounding Baseline for Recognition
inferredcites →https://doi.org/10.1109/iccv.1999.790410openalex-snapshot
Object recognition from local scale-invariant features
inferredcites →https://doi.org/10.1109/ictai.2012.119openalex-snapshot
Petroglyph Recognition Using Self-Organizing Maps and Fuzzy Visual Language Parsing
inferredcites →https://doi.org/10.1109/ijcnn.2012.6252544openalex-snapshot
Transfer learning for Latin and Chinese characters with Deep Neural Networks
inferredcites →https://doi.org/10.1109/msp.2015.2411291openalex-snapshot
Multimedia Analysis and Access of Ancient Maya Epigraphy: Tools to support scholars on Maya hieroglyphics
inferredcites →https://doi.org/10.1109/tmi.2016.2535302openalex-snapshot
Convolutional Neural Networks for Medical Image Analysis: Full Training or Fine Tuning?
inferredcites →https://doi.org/10.1109/tmm.2015.2477680openalex-snapshot
Multi-Task CNN Model for Attribute Prediction
inferredcites →https://doi.org/10.1109/tmm.2017.2755985openalex-snapshot
Maya Codical Glyph Segmentation: A Crowdsourcing Approach
inferredcites →https://doi.org/10.1145/2185520.2185540openalex-snapshot
How do humans sketch objects?
inferredcites →https://doi.org/10.1145/2425333.2425399openalex-snapshot
Automated petroglyph image segmentation with interactive classifier fusion
inferredcites →https://doi.org/10.1145/2502081.2502199openalex-snapshot
Automatic Egyptian hieroglyph recognition by retrieving images as texts
inferredcites →https://doi.org/10.1145/2905369openalex-snapshot
Evaluating Shape Representations for Maya Glyph Classification
inferredcites →https://doi.org/10.1145/3065386openalex-snapshot
ImageNet classification with deep convolutional neural networks
inferredcites →https://doi.org/10.1145/3095713.3095719openalex-snapshot
The 3D-Pitoti Dataset
inferredcites →https://doi.org/10.1145/3095713.3095746openalex-snapshot
Shape Representations for Maya Codical Glyphs
inferredcites →https://doi.org/10.2307/502055openalex-snapshot
A Catalog of Maya Hieroglyphs. By J. Eric S. Thompson.
inferredcites →https://doi.org/10.4230/oasics.dx.2026.15openalex-snapshot
AutoResearch Lite: a reproducible paper-inspired experiment runner (Adam mechanism reproduction and convergence-speed comparison)
inferredcites →https://doi.org/10.48550/arxiv.1207.0580openalex-snapshot
Improving neural networks by preventing co-adaptation of feature detectors
inferredcites →https://doi.org/10.48550/arxiv.1310.1531openalex-snapshot
DeCAF: A Deep Convolutional Activation Feature for Generic Visual Recognition
inferredcites →https://doi.org/10.48550/arxiv.1409.1556openalex-snapshot
Very Deep Convolutional Networks for Large-Scale Image Recognition
inferredcites →https://doi.org/10.48550/arxiv.1611.07450openalex-snapshot
Grad-CAM: Why did you say that?
inferredcites →https://doi.org/10.57702/o9raffedopenalex-snapshot
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1007/978-3-032-39028-8_11openalex-snapshot
Similarity-Based Retrieval of Maya Glyph Signs from Epigraphic Catalogues Using DINOv3 Embeddings
inferred← citeshttps://doi.org/10.1007/978-981-15-5856-6_64openalex-snapshot
Identification of Construction Era for Indian Subcontinent Ancient and Heritage Buildings by Using Deep Learning
inferred← citeshttps://doi.org/10.1007/978-981-95-4861-3_38openalex-snapshot
Exploring GenAI’s Role in Cultural Heritage Activation and Engagement at the Dunhuang Mogao Cave Exhibition
inferred← citeshttps://doi.org/10.1007/s10502-021-09358-zopenalex-snapshot
Decoding the Cauzin Softstrip: a case study in extracting information from old media
inferred← citeshttps://doi.org/10.1007/s11042-023-17844-yopenalex-snapshot
LanT: finding experts for digital calligraphy character restoration
inferred← citeshttps://doi.org/10.1016/j.iswa.2025.200562openalex-snapshot
Neural network for archaeological glyph detection
inferred← citeshttps://doi.org/10.1016/j.jas.2019.104998openalex-snapshot
Convolutional neural networks for archaeological site detection – Finding “princely” tombs
inferred← citeshttps://doi.org/10.1016/j.jocs.2021.101486openalex-snapshot
A deep neural network based framework for restoring the damaged persian pottery via digital inpainting
inferred← citeshttps://doi.org/10.1088/1757-899x/617/1/012016openalex-snapshot
Heritage Building Era Detection using CNN
inferred← citeshttps://doi.org/10.1109/access.2023.3280639openalex-snapshot
Digital Restoration of Cultural Heritage With Data-Driven Computing: A Survey
inferred← citeshttps://doi.org/10.1109/icpr48806.2021.9413255openalex-snapshot
A Few-shot Learning Approach for Historical Ciphered Manuscript Recognition
inferred← citeshttps://doi.org/10.1145/3284388openalex-snapshot
Improved Hieroglyph Representation for Image Retrieval
inferred← citeshttps://doi.org/10.1145/3465629openalex-snapshot
Deep Segmentation of Corrupted Glyphs
inferred← citeshttps://doi.org/10.1145/3641023openalex-snapshot
The State of Pilot Study Reporting in Crowdsourcing: A Reflection on Best Practices and Guidelines
inferred← citeshttps://doi.org/10.3390/buildings15203705openalex-snapshot
ConvNeXt-L-Based Recognition of Decorative Patterns in Historical Architecture: A Case Study of Macau
inferred← citeshttps://doi.org/10.55003/cast.2022.02.22.002openalex-snapshot
Using Deep Learning for the Image Recognition of Motifs on the Center of Sukhothai Ceramics
Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.