Evolution and Learning in Neural Networks. - Ron Keesing; David G. Stork (NIPS, 1990)

Book Review: "Artificial Neural Systems: Foundations, Paradigms, Applications, and Implementations", Patrick K. Simpson. - David G. Stork (Int. J. Neural Syst., 1990)

Network Generalization for Production: Learning and Producing Styled Letterforms. - Igor Grebert; David G. Stork; Ron Keesing; Steve Mims (NIPS, 1991)

Retinogeniculate Development: The Role of Competition and Correlated Retinal Activity. - Ron Keesing; David G. Stork; Carla J. Shatz (NIPS, 1991)

Book Review: "Introduction to the Theory of Neural Computation", John Hertz, Anders Krogh, and Richard G. Palmer. - David G. Stork (Int. J. Neural Syst., 1991)

Sources of Neural Structure in Speech and Language Processing. - David G. Stork (Int. J. Neural Syst., 1991)

Book Review: "Evolution of the First Nervous Systems", Peter A. V. Anderson (ed.). - David G. Stork (Int. J. Neural Syst., 1991)

Deterministic Boltzmann machine VLSI can be scaled using multi-chip modules. - Michael Murray; James B. Burr; David G. Stork; Ming-Tak Leung; Kan Boonyanit; Gregory J. Wolff; Allen M. Peterson (ASAP, 1992)

Second Order Derivatives for Network Pruning: Optimal Brain Surgeon. - Babak Hassibi; David G. Stork (NIPS, 1992)

Connectionist generalization for production: An example from GridFont. - Igor Grebert; David G. Stork; Ron Keesing; Steve Mims (Neural Networks, 1992)

How to solve the N-bit parity problem with two hidden units. - David G. Stork; James D. Allen (Neural Networks, 1992)

Optimal Brain Surgeon and general network pruning. - Babak Hassibi; David G. Stork; Gregory J. Wolff (ICNN, 1993)

Optimal Brain Surgeon: Extensions and performance comparison. - Babak Hassibi; David G. Stork; Gregory J. Wolff (NIPS, 1993)

Digital Boltzmann VLSI for Constraint Satisfaction and Learning. - 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 (NIPS, 1993)

Lipreading by Neural Networks: Visual Preprocessing, Learning, and Sensory Integration. - Gregory J. Wolff; K. Venkatesh Prasad; David G. Stork; Marcus E. Hennecke (NIPS, 1993)

How to solve the N-bit encoder problem with just one hidden unit. - David G. Stork; James D. Allen (Neurocomputing, 1993)

Letter to the editor. - David G. Stork (Neural Networks, 1993)

A Rapid Graph-based Method for Arbitrary Transformation-Invariant Pattern Classification. - Alessandro Sperduti; David G. Stork (NIPS, 1994)

Book Review: Handbook of Pattern Recognition & Computer Vision, Edited by C. H. Chen, L. F. Pau and P. S. P. Wang. - David G. Stork (Int. J. Neural Syst., 1994)

Optimizing bit-plane context-dependent entropy coding for palettized images. - Ahmad Zandi; David G. Stork; James D. Allen (ICIP, 1995)

Invited Speech: "Speechreading: An Overview of Image Processing, Feature Extraction, Sensory Intergration and Pattern Recognition Techiques. - David G. Stork; Marcus E. Hennecke (FG, 1996)

Empirical error-confidence Curves for Neural Network and Gaussian Classifiers. - Gregory J. Wolff; David G. Stork; Art B. Owen (Int. J. Neural Syst., 1996)

Happy Birthday, HAL! - David G. Stork (Computer, 1997)

From HAL to Office Appliances: Human-machine Interfaces in Science Fiction and Reality. - David G. Stork (IUI, 1998)

Generic object recognition using form and function - By louise stark and kevin bowyer. World scientic, 1996. - David G. Stork (Pattern Anal. Appl., 1998)

Character and Document Research in the Open Mind Initiative. - David G. Stork (ICDAR, 1999)

Building intelligent systems one e-citizen at a time. - Marti A. Hearst; Robin D. Hunson; David G. Stork (IEEE Intell. Syst., 1999)

Block Color Quantization: A New Method for Color Halftoning. - Maya R. Gupta; Michael J. Gormish; David G. Stork (ICIP, 2000)

Is paperless really more? - Ziming Liu; David G. Stork (Commun. ACM, 2000)

Using Open Data Collection for Intelligent Software. - David G. Stork (Computer, 2000)

Pattern classification, 2nd Edition. - Richard O. Duda; Peter E. Hart; David G. Stork (Wiley, 2001)

Toward a Computational Theory of Data Acquisition and Truthing. - David G. Stork (COLT/EuroCOLT, 2001)

An Architecture Supporting the Collection and Monitoring of Data Openly Contributed over the World Wide Web. - David G. Stork (WETICE, 2001)

Keynote address: the HAL 9000 computer and the vision of 2001: a space odyssey. - David G. Stork (WSC, 2001)

Token-Controlled Place Refinement in Hierarchical Petri Nets with Application to Active Document Workflow. - David G. Stork; Rob J. van Glabbeek (ICATPN, 2002)

Query Nets: Interacting Workflow Modules That Ensure Global Termination. - Rob J. van Glabbeek; David G. Stork (Business Process Management, 2003)

Evaluating Classifiers by Means of Test Data with Noisy Labels. - Chuck P. Lam; David G. Stork (IJCAI, 2003)

Illumination and Color in the Hockney Theory of Renaissance Painting Praxis: A Critical Evaluation. - David G. Stork (CIC, 2003)

Did Jan van Eyck build the first photocopier in 1432? - David G. Stork (Color Imaging: Processing, Hardcopy, and Applications, 2004)

Did the great masters use optical projections while painting? Perspective Comparison of Paintings and Photographs of Renaissance Chandeliers. - Antonio Criminisi; David G. Stork (ICPR (4), 2004)

Toward Optimal Labeling Strategy under Multiple Unreliable Labelers. - Chuck P. Lam; David G. Stork (AAAI Spring Symposium: Knowledge Collection from Volunteer Contributors, 2005)

Did Georges de la Tour use optical projections while painting Christ in the Carpenter's Studio? - David G. Stork (Electronic Imaging: Image and Video Communications and Processing, 2005)

Asymmetry in Lotto carpets and its implication for Hockney's optical projection theory. - David G. Stork (Human Vision and Electronic Imaging, 2005)

Estimating the location of illuminants in realist master paintings Computer image analysis addresses a debate in art history of the Baroque. - David G. Stork; M. Kimo Johnson (ICPR (1), 2006)

Computer Vision, Image Analysis, and Master Art: Part 1. - David G. Stork (IEEE Multim., 2006)

Computer Vision, Image Analysis, and Master Art: Part 2. - David G. Stork; Micah K. Johnson (IEEE Multim., 2006)

Computer Vision, Image Analysis, and Master Art: Part 3. - David G. Stork; Marco F. Duarte (IEEE Multim., 2007)

Revisiting Computer Image Analysis and Art. - David G. Stork; Marco F. Duarte (IEEE Multim., 2007)

Book Review: "complexity Management in Fuzzy Systems: a Rule Base Compression Approach", Alexander Gegov. - David G. Stork (Int. J. Comput. Intell. Appl., 2008)

From Digital Imaging to Computer Image Analysis of Fine Art. - David G. Stork (ArtsIT, 2009)

Finding Intrinsic and Extrinsic Viewing Parameters from a Single Realist Painting. - Tadeusz Jordan; David G. Stork; Wai L. Khoo; Zhigang Zhu 001 (CAIP, 2009)

Computer Vision and Computer Graphics Analysis of Paintings and Drawings: An Introduction to the Literature. - David G. Stork (CAIP, 2009)

Estimating the position of illuminants in paintings under weak model assumptions: an application to the works of two Baroque masters. - David C. Kale; David G. Stork (Human Vision and Electronic Imaging, 2009)

Painted or printed? Correlation analysis of the brickwork in Jan van der Heyden's View of Oudezijds Voorburgwal with the Oude Kerke in Amsterdam. - David G. Stork; Sean Meador; Petria Nobel (Human Vision and Electronic Imaging, 2009)

Computer Analysis of Lighting in Realist Master Art: Current Methods and Future Challenges. - David G. Stork (ICIAP, 2009)

New image processing challenges for jointly designed electro-optical imaging systems. - M. Dirk Robinson; David G. Stork (ICIP, 2009)

Lighting analysis of diffusely illuminated tableaus in realist paintings: an application to detecting "compositing" in the portraits of Garth Herrick. - David G. Stork; Micah K. Johnson (Media Forensics and Security, 2009)

Boosting multi-feature visual texture classiffiers for the authentication of Jackson Pollock's drip paintings. - Mahmoud Al-Ayyoub; Mohammad T. Irfan; David G. Stork (Computer Vision and Image Analysis of Art, 2011)

Improved curvature-based inpainting applied to fine art: recovering van Gogh's partially hidden brush strokes. - Yubin Kuang; David G. Stork; Fredrik Kahl (Computer Vision and Image Analysis of Art, 2011)

Computer analysis of lighting style in fine art: steps towards inter-artist studies. - David G. Stork (Computer Vision and Image Analysis of Art, 2011)

Did Caravaggio employ optical projections? An image analysis of the parity in the artist's paintings. - David G. Stork (Computer Vision and Image Analysis of Art, 2011)

A computer graphics reconstruction and optical analysis of scale anomalies in Caravaggio's Supper at Emmaus. - David G. Stork; Yasuo Furuichi (Computer Vision and Image Analysis of Art, 2011)

X-ray image analysis of Lorenzo Lotto's Husband and wife. - David G. Stork; Alexander J. Kossolapov (Computer Vision and Image Analysis of Art, 2011)

Improved methods for dewarping images in convex mirrors in fine art: applications to van Eyck and Parmigianino. - Yumi Usami; David G. Stork; Jun Fujiki; Hideitsu Hino; Shotaro Akaho; Noboru Murata (Computer Vision and Image Analysis of Art, 2011)

Mapping colors from paintings to tapestries: rejuvenating the faded colors in tapestries based on colors in reference paintings. - Marie Ström; Eija Johansson; David G. Stork (Human Vision and Electronic Imaging, 2012)

In search of Leonardo: computer-based facial image analysis of Renaissance artworks for identifying Leonardo as subject. - Christopher W. Tyler; William A. P. Smith; David G. Stork (Human Vision and Electronic Imaging, 2012)

Multichannel sampling of low light level scenes with unknown shifts. - Junjun Zhang; Feng Yang; Thomas Vogelsang; David G. Stork; Martin Vetterli (ICIP, 2013)

Hardware validated unified model of multibit temporally and spatially oversampled image sensors with conditional reset. - Thomas Vogelsang; David G. Stork; Michael Guidash (J. Electronic Imaging, 2014)

Miniature lensless computational infrared imager. - Evan Erickson; Mark Kellam; Patrick R. Gill; James Tringali; David G. Stork (IMSE, 2016)

Computational diffractive sensing and imaging: using optics for computation & computation for optics. - David G. Stork (SIGGRAPH ASIA Courses, 2016)

Special-purpose optics to reduce power dissipation in computational sensing and imaging systems. - David G. Stork; Patrick R. Gill (IEEE SENSORS, 2017)

Reducing electrical power dissipation in computational imaging systems through special-purpose optics. - David G. Stork; Thomas Vogelsang; James Tringali; Patrick R. Gill; Mark Kellam; Evan Erickson (ISCAS, 2017)

ACM SIGAI activity report. - 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; et al. (AI Matters, 2017)

ACM SIGAI activity report. - Sven Koenig; Sanmay Das; Rosemary D. Paradis; John P. Dickerson; Yolanda Gil; Katherine Guo; Benjamin Kuipers; Hang Ma 001; Nicholas Mattei; Amy McGovern; Larry R. Medsker; Todd W. Neller; et al. (AI Matters, 2018)

ACM SIGAI activity report. - Sven Koenig; Sanmay Das; Rosemary D. Paradis; John P. Dickerson; Yolanda Gil; Katherine Guo; Benjamin Kuipers; Iolanda Leite; Hang Ma 001; Nicholas Mattei; Amy McGovern; Larry R. Medsker; et al. (AI Matters, 2019)

Recovery of underdrawings and ghost-paintings via style transfer by deep convolutional neural networks: A digital tool for art scholars. - Anthony Bourached; George H. Cann; Ryan-Rhys Griffiths; David G. Stork (Computer Vision and Image Analysis of Art, 2021)

Resolution enhancement in the recovery of underdrawings via style transfer by generative adversarial deep neural networks. - George H. Cann; Anthony Bourached; Ryan-Rhys Griffiths; David G. Stork (Computer Vision and Image Analysis of Art, 2021)

Computational identification of significant actors in paintings through symbols and attributes. - David G. Stork; Anthony Bourached; George H. Cann; Ryan-Rhys Griffiths (Computer Vision and Image Analysis of Art, 2021)

Did Tim Paint a Vermeer? - David G. Stork; Christopher W. Tyler; Sara J. Schechner (Computer Vision and Image Analysis of Art, 2021)

Improving semantic segmentation of fine art images using photographs rendered in a style learned from artworks. - Thomas Heitzinger; David G. Stork (Computer Vision and Image Analysis of Art, 2022)

Artist-specific style transfer for semantic segmentation of paintings: The value of large corpora of surrogate artworks. - Thomas Heitzinger; Matthias Wödlinger; David G. Stork (Computer Vision and Image Analysis of Art, 2022)

Extracting associations and meanings of objects depicted in artworks through bi-modal deep networks. - Gregory Kell; Ryan-Rhys Griffiths; Anthony Bourached; David G. Stork (Computer Vision and Image Analysis of Art, 2022)

Automatic Computation of Meaning in Authored Images Such as Artworks: A Grand Challenge for AI. - David G. Stork (ACM Journal on Computing and Cultural Heritage, 2022)

Deep neural network-based detection of counterfeit products from smartphone images. - Hugo Garcia-Cotte; Dorra Mellouli; Abdul Rehman; Li Wang; David G. Stork (CoRR, 2024)

Computer Vision, ML, and AI in the Study of Fine Art. - David G. Stork (Commun. ACM, 2024)