David G. Stork

Publication Activity (10 Years)

Years Active: 1990-2024
Publications (10 Years): 20

Top Topics

Imaging Systems

Discontinuity Preserving

Semantic Segmentation

Resolution Enhancement

Top Venues

Computer Vision and Image Analysis of Art

ACM Journal on Computing and Cultural Heritage

Publications

David G. Stork
Computer Vision, ML, and AI in the Study of Fine Art. Commun. ACM 67 (5) (2024)
Thomas Heitzinger, David G. Stork
Improving semantic segmentation of fine art images using photographs rendered in a style learned from artworks. Computer Vision and Image Analysis of Art (2022)
Gregory Kell, Ryan-Rhys Griffiths, Anthony Bourached, David G. Stork
Extracting associations and meanings of objects depicted in artworks through bi-modal deep networks. Computer Vision and Image Analysis of Art (2022)
Thomas Heitzinger, Matthias Wödlinger, David G. Stork
Artist-specific style transfer for semantic segmentation of paintings: The value of large corpora of surrogate artworks. Computer Vision and Image Analysis of Art (2022)
David G. Stork
Automatic Computation of Meaning in Authored Images Such as Artworks: A Grand Challenge for AI. ACM Journal on Computing and Cultural Heritage 15 (4) (2022)
Gregory Kell, Ryan-Rhys Griffiths, Anthony Bourached, David G. Stork
Extracting associations and meanings of objects depicted in artworks through bi-modal deep networks. CoRR (2022)
David G. Stork, Christopher W. Tyler, Sara J. Schechner
Did Tim Paint a Vermeer? Computer Vision and Image Analysis of Art (2021)
David G. Stork, Anthony Bourached, George H. Cann, Ryan-Rhys Griffiths
Computational identification of significant actors in paintings through symbols and attributes. Computer Vision and Image Analysis of Art (2021)
Anthony Bourached, George Cann, Ryan-Rhys Griffiths, David G. Stork
Recovery of underdrawings and ghost-paintings via style transfer by deep convolutional neural networks: A digital tool for art scholars. CoRR (2021)
George H. Cann, Anthony Bourached, Ryan-Rhys Griffiths, David G. Stork
Resolution enhancement in the recovery of underdrawings via style transfer by generative adversarial deep neural networks. Computer Vision and Image Analysis of Art (2021)
George Cann, Anthony Bourached, Ryan-Rhys Griffiths, David G. Stork
Resolution enhancement in the recovery of underdrawings via style transfer by generative adversarial deep neural networks. CoRR (2021)
Anthony Bourached, George H. Cann, Ryan-Rhys Griffiths, David G. Stork
Recovery of underdrawings and ghost-paintings via style transfer by deep convolutional neural networks: A digital tool for art scholars. Computer Vision and Image Analysis of Art (2021)
David G. Stork, Anthony Bourached, George H. Cann, Ryan-Rhys Griffiths
Computational identification of significant actors in paintings through symbols and attributes. CoRR (2021)
Sven Koenig, Sanmay Das, Rosemary D. Paradis, John P. Dickerson, Yolanda Gil, Katherine Guo, Benjamin Kuipers, Iolanda Leite, Hang Ma, Nicholas Mattei, Amy McGovern, Larry R. Medsker, Todd W. Neller, Marion Neumann, Plamen Petrov, Michael Rovatsos, David G. Stork
ACM SIGAI activity report. AI Matters 5 (3) (2019)
Sven Koenig, Sanmay Das, Rosemary D. Paradis, John P. Dickerson, Yolanda Gil, Katherine Guo, Benjamin Kuipers, Hang Ma, Nicholas Mattei, Amy McGovern, Larry R. Medsker, Todd W. Neller, Plamen Petrov, Michael Rovatsos, David G. Stork
ACM SIGAI activity report. AI Matters 4 (3) (2018)
David G. Stork, Patrick R. Gill
Special-purpose optics to reduce power dissipation in computational sensing and imaging systems. IEEE SENSORS (2017)
Sven Koenig, Sanmay Das, Rosemary D. Paradis, Eric Eaton, Yolanda Gil, Katherine Guo, Bojun Huang, Albert Jiang, Benjamin Kuipers, Nicholas Mattei, Amy McGovern, Larry R. Medsker, Todd W. Neller, Plamen Petrov, Michael Rovatsos, David G. Stork
ACM SIGAI activity report. AI Matters 3 (3) (2017)
David G. Stork, Thomas Vogelsang, James Tringali, Patrick R. Gill, Mark Kellam, Evan Erickson
Reducing electrical power dissipation in computational imaging systems through special-purpose optics. ISCAS (2017)
Evan Erickson, Mark Kellam, Patrick R. Gill, James Tringali, David G. Stork
Miniature lensless computational infrared imager. IMSE (2016)
David G. Stork
Computational diffractive sensing and imaging: using optics for computation & computation for optics. SIGGRAPH ASIA Courses (2016)
Thomas Vogelsang, David G. Stork, Michael Guidash
Hardware validated unified model of multibit temporally and spatially oversampled image sensors with conditional reset. J. Electronic Imaging 23 (1) (2014)
Junjun Zhang, Feng Yang, Thomas Vogelsang, David G. Stork, Martin Vetterli
Multichannel sampling of low light level scenes with unknown shifts. ICIP (2013)
Christopher W. Tyler, William A. P. Smith, David G. Stork
In search of Leonardo: computer-based facial image analysis of Renaissance artworks for identifying Leonardo as subject. Human Vision and Electronic Imaging (2012)
Marie Ström, Eija Johansson, David G. Stork
Mapping colors from paintings to tapestries: rejuvenating the faded colors in tapestries based on colors in reference paintings. Human Vision and Electronic Imaging (2012)
Yubin Kuang, David G. Stork, Fredrik Kahl
Improved curvature-based inpainting applied to fine art: recovering van Gogh's partially hidden brush strokes. Computer Vision and Image Analysis of Art (2011)
David G. Stork, Yasuo Furuichi
A computer graphics reconstruction and optical analysis of scale anomalies in Caravaggio's Supper at Emmaus. Computer Vision and Image Analysis of Art (2011)
David G. Stork, Alexander J. Kossolapov
X-ray image analysis of Lorenzo Lotto's Husband and wife. Computer Vision and Image Analysis of Art (2011)
David G. Stork
Did Caravaggio employ optical projections? An image analysis of the parity in the artist's paintings. Computer Vision and Image Analysis of Art (2011)
David G. Stork
Computer analysis of lighting style in fine art: steps towards inter-artist studies. Computer Vision and Image Analysis of Art (2011)
Yumi Usami, David G. Stork, Jun Fujiki, Hideitsu Hino, Shotaro Akaho, Noboru Murata
Improved methods for dewarping images in convex mirrors in fine art: applications to van Eyck and Parmigianino. Computer Vision and Image Analysis of Art (2011)
Mahmoud Al-Ayyoub, Mohammad T. Irfan, David G. Stork
Boosting multi-feature visual texture classiffiers for the authentication of Jackson Pollock's drip paintings. Computer Vision and Image Analysis of Art (2011)
David G. Stork
From Digital Imaging to Computer Image Analysis of Fine Art. ArtsIT (2009)
Tadeusz Jordan, David G. Stork, Wai L. Khoo, Zhigang Zhu
Finding Intrinsic and Extrinsic Viewing Parameters from a Single Realist Painting. CAIP (2009)
David G. Stork, Micah K. Johnson
Lighting analysis of diffusely illuminated tableaus in realist paintings: an application to detecting "compositing" in the portraits of Garth Herrick. Media Forensics and Security (2009)
David G. Stork
Computer Vision and Computer Graphics Analysis of Paintings and Drawings: An Introduction to the Literature. CAIP (2009)
David G. Stork, Sean Meador, Petria Nobel
Painted or printed? Correlation analysis of the brickwork in Jan van der Heyden's View of Oudezijds Voorburgwal with the Oude Kerke in Amsterdam. Human Vision and Electronic Imaging (2009)
M. Dirk Robinson, David G. Stork
New image processing challenges for jointly designed electro-optical imaging systems. ICIP (2009)
David G. Stork
Computer Analysis of Lighting in Realist Master Art: Current Methods and Future Challenges. ICIAP (2009)
David C. Kale, David G. Stork
Estimating the position of illuminants in paintings under weak model assumptions: an application to the works of two Baroque masters. Human Vision and Electronic Imaging (2009)
David G. Stork
Book Review: "complexity Management in Fuzzy Systems: a Rule Base Compression Approach", Alexander Gegov. Int. J. Comput. Intell. Appl. 7 (1) (2008)
David G. Stork, Marco F. Duarte
Revisiting Computer Image Analysis and Art. IEEE Multim. 14 (3) (2007)
David G. Stork, Marco F. Duarte
Computer Vision, Image Analysis, and Master Art: Part 3. IEEE Multim. 14 (1) (2007)
David G. Stork, M. Kimo Johnson
Estimating the location of illuminants in realist master paintings Computer image analysis addresses a debate in art history of the Baroque. ICPR (1) (2006)
David G. Stork, Micah K. Johnson
Computer Vision, Image Analysis, and Master Art: Part 2. IEEE Multim. 13 (4) (2006)
David G. Stork
Computer Vision, Image Analysis, and Master Art: Part 1. IEEE Multim. 13 (3) (2006)
David G. Stork
Asymmetry in Lotto carpets and its implication for Hockney's optical projection theory. Human Vision and Electronic Imaging (2005)
Chuck P. Lam, David G. Stork
Toward Optimal Labeling Strategy under Multiple Unreliable Labelers. AAAI Spring Symposium: Knowledge Collection from Volunteer Contributors (2005)
David G. Stork
Did Georges de la Tour use optical projections while painting Christ in the Carpenter's Studio? Electronic Imaging: Image and Video Communications and Processing (2005)
David G. Stork
Did Jan van Eyck build the first photocopier in 1432? Color Imaging: Processing, Hardcopy, and Applications (2004)
Antonio Criminisi, David G. Stork
Did the great masters use optical projections while painting? Perspective Comparison of Paintings and Photographs of Renaissance Chandeliers. ICPR (4) (2004)
Chuck P. Lam, David G. Stork
Evaluating Classifiers by Means of Test Data with Noisy Labels. IJCAI (2003)
Rob J. van Glabbeek, David G. Stork
Query Nets: Interacting Workflow Modules That Ensure Global Termination. Business Process Management (2003)
David G. Stork
Illumination and Color in the Hockney Theory of Renaissance Painting Praxis: A Critical Evaluation. Color Imaging Conference (2003)
David G. Stork, Rob J. van Glabbeek
Token-Controlled Place Refinement in Hierarchical Petri Nets with Application to Active Document Workflow. ICATPN (2002)
David G. Stork
Toward a Computational Theory of Data Acquisition and Truthing. COLT/EuroCOLT (2001)
David G. Stork
: a space odyssey. WSC (2001)
David G. Stork
An Architecture Supporting the Collection and Monitoring of Data Openly Contributed over the World Wide Web. WETICE (2001)
David G. Stork
Using Open Data Collection for Intelligent Software. Computer 33 (10) (2000)
Ziming Liu, David G. Stork
Is paperless really more? Commun. ACM 43 (11) (2000)
Maya R. Gupta, Michael J. Gormish, David G. Stork
Block Color Quantization: A New Method for Color Halftoning. ICIP (2000)
Marti A. Hearst, Robin D. Hunson, David G. Stork
Building intelligent systems one e-citizen at a time. IEEE Intell. Syst. 14 (3) (1999)
David G. Stork
Character and Document Research in the Open Mind Initiative. ICDAR (1999)
David G. Stork
. World scientic, 1996. Pattern Anal. Appl. 1 (2) (1998)
David G. Stork
From HAL to Office Appliances: Human-machine Interfaces in Science Fiction and Reality. IUI (1998)
David G. Stork
Happy Birthday, HAL! Computer 30 (1) (1997)
Gregory J. Wolff, David G. Stork, Art B. Owen
Empirical error-confidence Curves for Neural Network and Gaussian Classifiers. Int. J. Neural Syst. 7 (3) (1996)
David G. Stork, Marcus E. Hennecke
Invited Speech: "Speechreading: An Overview of Image Processing, Feature Extraction, Sensory Intergration and Pattern Recognition Techiques. FG (1996)
Ahmad Zandi, David G. Stork, James D. Allen
Optimizing bit-plane context-dependent entropy coding for palettized images. ICIP (1995)
Alessandro Sperduti, David G. Stork
A Rapid Graph-based Method for Arbitrary Transformation-Invariant Pattern Classification. NIPS (1994)
David G. Stork
Book Review: Handbook of Pattern Recognition & Computer Vision, Edited by C. H. Chen, L. F. Pau and P. S. P. Wang. Int. J. Neural Syst. 5 (3) (1994)
David G. Stork, James D. Allen
-bit encoder problem with just one hidden unit. Neurocomputing 5 (2) (1993)
Babak Hassibi, David G. Stork, Gregory J. Wolff
Optimal Brain Surgeon: Extensions and performance comparison. NIPS (1993)
Babak Hassibi, David G. Stork, Gregory J. Wolff
Optimal Brain Surgeon and general network pruning. ICNN (1993)
David G. Stork
Letter to the editor. Neural Networks 6 (5) (1993)
Michael Murray, Ming-Tak Leung, Kan Boonyanit, Kong Kritayakirana, James B. Burr, Gregory J. Wolff, Tokahiro Watanabe, Edward L. Schwartz, David G. Stork, Allen M. Peterson
Digital Boltzmann VLSI for Constraint Satisfaction and Learning. NIPS (1993)
Gregory J. Wolff, K. Venkatesh Prasad, David G. Stork, Marcus E. Hennecke
Lipreading by Neural Networks: Visual Preprocessing, Learning, and Sensory Integration. NIPS (1993)
David G. Stork, James D. Allen
How to solve the N-bit parity problem with two hidden units. Neural Networks 5 (6) (1992)
Michael Murray, James B. Burr, David G. Stork, Ming-Tak Leung, Kan Boonyanit, Gregory J. Wolff, Allen M. Peterson
Deterministic Boltzmann machine VLSI can be scaled using multi-chip modules. ASAP (1992)
Igor Grebert, David G. Stork, Ron Keesing, Steve Mims
Connectionist generalization for production: An example from GridFont. Neural Networks 5 (4) (1992)
Babak Hassibi, David G. Stork
Second Order Derivatives for Network Pruning: Optimal Brain Surgeon. NIPS (1992)
Igor Grebert, David G. Stork, Ron Keesing, Steve Mims
Network Generalization for Production: Learning and Producing Styled Letterforms. NIPS (1991)
David G. Stork
Book Review: "Introduction to the Theory of Neural Computation", John Hertz, Anders Krogh, and Richard G. Palmer. Int. J. Neural Syst. 2 (1-2) (1991)
Ron Keesing, David G. Stork, Carla J. Shatz
Retinogeniculate Development: The Role of Competition and Correlated Retinal Activity. NIPS (1991)
David G. Stork
Sources of Neural Structure in Speech and Language Processing. Int. J. Neural Syst. 2 (3) (1991)
David G. Stork
Book Review: "Evolution of the First Nervous Systems", Peter A. V. Anderson (ed.). Int. J. Neural Syst. 2 (4) (1991)
Ron Keesing, David G. Stork
Evolution and Learning in Neural Networks. NIPS (1990)
David G. Stork
Book Review: "Artificial Neural Systems: Foundations, Paradigms, Applications, and Implementations", Patrick K. Simpson. Int. J. Neural Syst. 1 (3) (1990)