On the public citation graph

Deep Segmentation of Corrupted Glyphs

https://doi.org/10.1145/3465629
0 signed · 95 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 See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.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/10.1007/978-3-030-58539-6_11openalex-snapshot
Object-Contextual Representations for Semantic Segmentation
inferredcites →https://doi.org/10.1007/978-3-319-07998-1_56openalex-snapshot
Segmentation and Recognition of Petroglyphs Using Generic Fourier Descriptors
inferredcites →https://doi.org/10.1007/978-3-319-10602-1_48openalex-snapshot
Microsoft COCO: Common Objects in Context
inferredcites →https://doi.org/10.1007/978-3-319-24574-4_28openalex-snapshot
U-Net: Convolutional Networks for Biomedical Image Segmentation
inferredcites →https://doi.org/10.1007/978-3-319-46448-0_5openalex-snapshot
Learning to Refine Object Segments
inferredcites →https://doi.org/10.1007/978-3-319-46466-4_32openalex-snapshot
Instance-Sensitive Fully Convolutional Networks
inferredcites →https://doi.org/10.1007/978-3-319-46475-6_42openalex-snapshot
Amodal Instance Segmentation
inferredcites →https://doi.org/10.1007/978-3-319-46487-9_43openalex-snapshot
Precomputed Real-Time Texture Synthesis with Markovian Generative Adversarial Networks
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/10.1007/978-3-319-54187-7_12openalex-snapshot
Removing Shadows from Images of Documents
inferredcites →https://doi.org/10.1007/978-3-642-33715-4_55openalex-snapshot
Beyond the Line of Sight: Labeling the Underlying Surfaces
inferredcites →https://doi.org/10.1007/978-3-642-39094-4_35openalex-snapshot
Shading Removal of Illustrated Documents
inferredcites →https://doi.org/10.1007/s10851-014-0506-3openalex-snapshot
Sliced and Radon Wasserstein Barycenters of Measures
inferredcites →https://doi.org/10.1007/s12021-018-9377-xopenalex-snapshot
SegAN: Adversarial Network with Multi-scale L1 Loss for Medical Image Segmentation
inferredcites →https://doi.org/10.1016/j.daach.2015.03.001openalex-snapshot
Automated classification of petroglyphs
inferredcites →https://doi.org/10.1016/j.patcog.2017.08.025openalex-snapshot
Binarization of degraded document images based on hierarchical deep supervised network
inferredcites →https://doi.org/10.1016/j.patcog.2018.08.011openalex-snapshot
A selectional auto-encoder approach for document image binarization
inferredcites →https://doi.org/10.1016/j.patrec.2017.07.014openalex-snapshot
Ensemble of steerable local neighbourhood grey-level information for binarization
inferredcites →https://doi.org/10.1016/j.patrec.2018.05.011openalex-snapshot
PDNet: Semantic segmentation integrated with a primal-dual network for document binarization
inferredcites →https://doi.org/10.1023/a:1026543900054openalex-snapshot
The Earth Mover's Distance as a Metric for Image Retrieval
inferredcites →https://doi.org/10.1109/aici.2010.66openalex-snapshot
Study on Printed Tibetan Character Recognition
inferredcites →https://doi.org/10.1109/cvpr.2006.305openalex-snapshot
The Layout Consistent Random Field for Recognizing and Segmenting Partially Occluded Objects
inferredcites →https://doi.org/10.1109/cvpr.2011.5995623openalex-snapshot
A segmentation-aware object detection model with occlusion handling
inferredcites →https://doi.org/10.1109/cvpr.2013.422openalex-snapshot
Occlusion Patterns for Object Class Detection
inferredcites →https://doi.org/10.1109/cvpr.2014.81openalex-snapshot
Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation
inferredcites →https://doi.org/10.1109/cvpr.2015.7298765openalex-snapshot
Learning to propose objects
inferredcites →https://doi.org/10.1109/cvpr.2015.7298965openalex-snapshot
Fully convolutional networks for semantic segmentation
inferredcites →https://doi.org/10.1109/cvpr.2016.343openalex-snapshot
Instance-Aware Semantic Segmentation via Multi-task Network Cascades
inferredcites →https://doi.org/10.1109/cvpr.2016.348openalex-snapshot
Efficient Piecewise Training of Deep Structured Models for Semantic Segmentation
inferredcites →https://doi.org/10.1109/cvpr.2016.350openalex-snapshot
The Cityscapes Dataset for Semantic Urban Scene Understanding
inferredcites →https://doi.org/10.1109/cvpr.2016.396openalex-snapshot
Attention to Scale: Scale-Aware Semantic Image Segmentation
inferredcites →https://doi.org/10.1109/cvpr.2016.79openalex-snapshot
Instance-Level Segmentation for Autonomous Driving with Deep Densely Connected MRFs
inferredcites →https://doi.org/10.1109/cvpr.2016.91openalex-snapshot
You Only Look Once: Unified, Real-Time Object Detection
inferredcites →https://doi.org/10.1109/cvpr.2017.320openalex-snapshot
Semantic Amodal Segmentation
inferredcites →https://doi.org/10.1109/cvpr.2017.632openalex-snapshot
Image-to-Image Translation with Conditional Adversarial Networks
inferredcites →https://doi.org/10.1109/cvpr.2017.70openalex-snapshot
Boundary-Aware Instance Segmentation
inferredcites →https://doi.org/10.1109/cvpr.2018.00422openalex-snapshot
MaskLab: Instance Segmentation by Refining Object Detection with Semantic and Direction Features
inferredcites →https://doi.org/10.1109/cvpr.2018.00643openalex-snapshot
SeGAN: Segmenting and Generating the Invisible
inferredcites →https://doi.org/10.1109/cvpr.2018.00913openalex-snapshot
Path Aggregation Network for Instance Segmentation
inferredcites →https://doi.org/10.1109/cvpr.2019.00904openalex-snapshot
Instance Segmentation by Jointly Optimizing Spatial Embeddings and Clustering Bandwidth
inferredcites →https://doi.org/10.1109/cvpr.2019.01090openalex-snapshot
Max-Sliced Wasserstein Distance and Its Use for GANs
inferredcites →https://doi.org/10.1109/cvpr.2019.01128openalex-snapshot
“Double-DIP”: Unsupervised Image Decomposition via Coupled Deep-Image-Priors
inferredcites →https://doi.org/10.1109/cvpr42600.2020.00385openalex-snapshot
BANet: Bidirectional Aggregation Network With Occlusion Handling for Panoptic Segmentation
inferredcites →https://doi.org/10.1109/cvpr42600.2020.01221openalex-snapshot
PolarMask: Single Shot Instance Segmentation With Polar Representation
inferredcites →https://doi.org/10.1109/das.2018.71openalex-snapshot
Document Image Binarization Using Recurrent Neural Networks
inferredcites →https://doi.org/10.1109/iccv.2015.162openalex-snapshot
Semantic Image Segmentation via Deep Parsing Network
inferredcites →https://doi.org/10.1109/iccv.2015.169openalex-snapshot
Fast R-CNN
inferredcites →https://doi.org/10.1109/iccv.2015.178openalex-snapshot
Learning Deconvolution Network for Semantic Segmentation
inferredcites →https://doi.org/10.1109/iccv.2015.179openalex-snapshot
Conditional Random Fields as Recurrent Neural Networks
inferredcites →https://doi.org/10.1109/iccv.2015.191openalex-snapshot
BoxSup: Exploiting Bounding Boxes to Supervise Convolutional Networks for Semantic Segmentation
inferredcites →https://doi.org/10.1109/iccv.2015.203openalex-snapshot
Weakly-and Semi-Supervised Learning of a Deep Convolutional Network for Semantic Image Segmentation
inferredcites →https://doi.org/10.1109/iccv.2017.322openalex-snapshot
Mask R-CNN
inferredcites →https://doi.org/10.1109/iccv.2017.606openalex-snapshot
Semi Supervised Semantic Segmentation Using Generative Adversarial Network
inferredcites →https://doi.org/10.1109/iccv.2019.00073openalex-snapshot
SSAP: Single-Shot Instance Segmentation With Affinity Pyramid
inferredcites →https://doi.org/10.1109/iccv.2019.00215openalex-snapshot
TensorMask: A Foundation for Dense Object Segmentation
inferredcites →https://doi.org/10.1109/icdar.2005.168openalex-snapshot
Neural based binarization techniques
inferredcites →https://doi.org/10.1109/icdar.2009.246openalex-snapshot
ICDAR 2009 Document Image Binarization Contest (DIBCO 2009)
inferredcites →https://doi.org/10.1109/icdar.2015.7333933openalex-snapshot
Deepdocclassifier: Document classification with deep Convolutional Neural Network
inferredcites →https://doi.org/10.1109/icdar.2017.121openalex-snapshot
Using Convolutional Encoder-Decoder for Document Image Binarization
inferredcites →https://doi.org/10.1109/icdar.2017.25openalex-snapshot
Document Image Binarization with Fully Convolutional Neural Networks
inferredcites →https://doi.org/10.1109/icdar.2019.00074openalex-snapshot
A Character Attention Generative Adversarial Network for Degraded Historical Document Restoration
inferredcites →https://doi.org/10.1109/icfhr.2010.118openalex-snapshot
H-DIBCO 2010 - Handwritten Document Image Binarization Competition
inferredcites →https://doi.org/10.1109/icfhr.2012.243openalex-snapshot
Occluded Character Restoration Using Active Contour with Shape Priors
inferredcites →https://doi.org/10.1109/icip.2016.7533063openalex-snapshot
Learning document image binarization from data
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/iraniancee.2016.7585772openalex-snapshot
Multi-label classification with feature-aware implicit encoding and generalized cross-entropy loss
inferredcites →https://doi.org/10.1109/tpami.2011.208openalex-snapshot
Layered Object Models for Image Segmentation
inferredcites →https://doi.org/10.1109/tpami.2015.2389824openalex-snapshot
Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition
inferredcites →https://doi.org/10.1109/tpami.2016.2644615openalex-snapshot
SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation
inferredcites →https://doi.org/10.1109/tpami.2017.2699184openalex-snapshot
DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs
inferredcites →https://doi.org/10.1109/tpami.2021.3059968openalex-snapshot
Image Segmentation Using Deep Learning: A Survey
inferredcites →https://doi.org/10.1145/2905369openalex-snapshot
Evaluating Shape Representations for Maya Glyph Classification
inferredcites →https://doi.org/10.1145/2950062openalex-snapshot
Interactive 3D Segmentation of Rock-Art by Enhanced Depth Maps and Gradient Preserving Regularization
inferredcites →https://doi.org/10.1145/3151509.3151515openalex-snapshot
Methods of data augmentation for palimpsest character recognition with Deep Neural Network
inferredcites →https://doi.org/10.1145/3230670openalex-snapshot
How to Tell Ancient Signs Apart? Recognizing and Visualizing Maya Glyphs with CNNs
inferredcites →https://doi.org/10.1145/3284388openalex-snapshot
Improved Hieroglyph Representation for Image Retrieval
inferredcites →https://doi.org/10.3390/arts2040225openalex-snapshot
Chronological Trends in Negev Rock Art: The Har Michia Petroglyphs as a Test Case
inferredcites →https://doi.org/10.3390/jimaging6100110openalex-snapshot
Deep Learning for Historical Document Analysis and Recognition—A Survey
inferredcites →https://doi.org/10.5244/c.30.15openalex-snapshot
A MultiPath Network for Object Detection
inferredcites →https://doi.org/10.5555/2722890.2723023openalex-snapshot
Binarization, character extraction, and writer identification of historical Hebrew calligraphy documents

What points at this work

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

inferred← citeshttps://doi.org/10.1007/978-3-031-41498-5_18openalex-snapshot
Reconstruction of Broken Writing Strokes in Greek Papyri
inferred← citeshttps://doi.org/10.1007/s11042-023-17844-yopenalex-snapshot
LanT: finding experts for digital calligraphy character restoration
inferred← citeshttps://doi.org/10.1007/s11042-025-20691-8openalex-snapshot
Delineating valuable content in Byzantine seals by combining deep learning and shape model of the border pattern
inferred← citeshttps://doi.org/10.1016/j.iswa.2025.200562openalex-snapshot
Neural network for archaeological glyph detection
inferred← citeshttps://doi.org/10.1080/15583058.2026.2686321openalex-snapshot
Evaluation of Petroglyphs Spalling Diseases in Helankou Based on FAHP and BP Neural Network
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/comp-sif65618.2025.10969917openalex-snapshot
UNet and Dense Extreme Inception Networks: A Unified Approach to Archeological Artifact Drawing Generation
inferred← citeshttps://doi.org/10.1109/iceccme64568.2025.11277699openalex-snapshot
From Pixels to Patterns: Artificial Intelligence and Digital Imaging for Rock Art Interpretation
inferred← citeshttps://doi.org/10.1109/wacv57701.2024.00710openalex-snapshot
ArcAid: Analysis of Archaeological Artifacts using Drawings
inferred← citeshttps://doi.org/10.1145/3477910openalex-snapshot
A Simple Algorithm for Optimal Search Trees with Two-way Comparisons
inferred← citeshttps://doi.org/10.1145/3694789openalex-snapshot
Repetitive Patterns Recognition in Textures of Ancient Peruvian Pottery
inferred← citeshttps://doi.org/10.1145/3746404openalex-snapshot
Integrating Textual-Based and Visual-Based Features in Poem Detection for Digitized Historical Newspaper Document Images
inferred← citeshttps://doi.org/10.1186/s40494-024-01366-3openalex-snapshot
Intelligent assessment system of material deterioration in masonry tower based on improved image segmentation model
inferred← citeshttps://doi.org/10.1515/opar-2025-0054openalex-snapshot
Everyone Has to Start Somewhere: Democratisation of Digital Documentation and Visualisation in 3D
inferred← citeshttps://doi.org/10.48084/etasr.18615openalex-snapshot
Towards the Automated Recognition of Ancient Sundanese Scripts: Groundtruth Generation at the Geusan Ulun Museum
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.