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David G. Stork
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2020 – today
- 2024
- [j26]David G. Stork:
Computer Vision, ML, and AI in the Study of Fine Art. Commun. ACM 67(5): 68-75 (2024) - 2022
- [j25]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): 1-11 (2022) - [c57]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: 1-5 - [c56]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: 1-6 - [c55]Gregory Kell, Ryan-Rhys Griffiths
Extracting associations and meanings of objects depicted in artworks through bi-modal deep networks. Computer Vision and Image Analysis of Art 2022: 1-14 - [e3]Kurt Heumiller, David G. Stork:
Computer Vision and Image Analysis of Art 2022, online, January 15-26, 2022. Society for Imaging Science and Technology 2022 [contents] - [i4]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 abs/2203.07026 (2022) - 2021
- [c54]Anthony Bourached, George H. Cann, Ryan-Rhys Griffiths
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: 1-10 - [c53]George H. Cann, Anthony Bourached, Ryan-Rhys Griffiths
Resolution enhancement in the recovery of underdrawings via style transfer by generative adversarial deep neural networks. Computer Vision and Image Analysis of Art 2021: 1-8 - [c52]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: 1-8 - [c51]David G. Stork, Christopher W. Tyler, Sara J. Schechner:
Did Tim Paint a Vermeer? Computer Vision and Image Analysis of Art 2021: 1-12 - [e2]Kurt Heumiller, David G. Stork:
Computer Vision and Image Analysis of Art 2021, online, January 11-28, 2021. Society for Imaging Science and Technology 2021 [contents] - [i3]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 abs/2101.10807 (2021) - [i2]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 abs/2102.00209 (2021) - [i1]David G. Stork, Anthony Bourached, George H. Cann, Ryan-Rhys Griffiths:
Computational identification of significant actors in paintings through symbols and attributes. CoRR abs/2102.02732 (2021)
2010 – 2019
- 2019
- [j24]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): 6-11 (2019) - 2018
- [j23]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): 7-11 (2018) - 2017
- [j22]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): 7-11 (2017) - [c50]David G. Stork, Patrick R. Gill:
Special-purpose optics to reduce power dissipation in computational sensing and imaging systems. IEEE SENSORS 2017: 1-3 - [c49]David G. Stork, Thomas Vogelsang
Reducing electrical power dissipation in computational imaging systems through special-purpose optics. ISCAS 2017: 1-4 - 2016
- [c48]Evan Erickson, Mark Kellam, Patrick R. Gill, James Tringali, David G. Stork:
Miniature lensless computational infrared imager. IMSE 2016: 1-4 - [c47]David G. Stork:
Computational diffractive sensing and imaging: using optics for computation & computation for optics. SIGGRAPH ASIA Courses 2016: 6:1-6:211 - 2014
- [j21]Thomas Vogelsang
Hardware validated unified model of multibit temporally and spatially oversampled image sensors with conditional reset. J. Electronic Imaging 23(1): 013021 (2014) - 2013
- [c46]Junjun Zhang, Feng Yang, Thomas Vogelsang
Multichannel sampling of low light level scenes with unknown shifts. ICIP 2013: 863-867 - 2012
- [c45]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: 82911F - [c44]Christopher W. Tyler, William A. P. Smith
In search of Leonardo: computer-based facial image analysis of Renaissance artworks for identifying Leonardo as subject. Human Vision and Electronic Imaging 2012: 82911D - 2011
- [c43]Mahmoud Al-Ayyoub, Mohammad T. Irfan
Boosting multi-feature visual texture classiffiers for the authentication of Jackson Pollock's drip paintings. Computer Vision and Image Analysis of Art 2011: 78690H - [c42]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: 78690I - [c41]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: 78690J - [c40]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: 78690K - [c39]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: 78690L - [c38]Yumi Usami, David G. Stork, Jun Fujiki, Hideitsu Hino
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: 78690F - [c37]David G. Stork:
Computer analysis of lighting style in fine art: steps towards inter-artist studies. Computer Vision and Image Analysis of Art 2011: 786903 - [e1]David G. Stork, Jim Coddington, Anna Bentkowska-Kafel:
Computer Vision and Image Analysis of Art II, San Francisco Airport, California, USA, January 23-27, 2011. SPIE Proceedings 7869, SPIE 2011, ISBN 9780819484062 [contents]
2000 – 2009
- 2009
- [c36]David G. Stork:
From Digital Imaging to Computer Image Analysis of Fine Art. ArtsIT 2009: 1-8 - [c35]David G. Stork:
Computer Vision and Computer Graphics Analysis of Paintings and Drawings: An Introduction to the Literature. CAIP 2009: 9-24 - [c34]Tadeusz Jordan, David G. Stork, Wai L. Khoo, Zhigang Zhu
Finding Intrinsic and Extrinsic Viewing Parameters from a Single Realist Painting. CAIP 2009: 293-300 - [c33]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: 72401 - [c32]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: 72401 - [c31]David G. Stork:
Computer Analysis of Lighting in Realist Master Art: Current Methods and Future Challenges. ICIAP 2009: 6-11 - [c30]M. Dirk Robinson, David G. Stork:
New image processing challenges for jointly designed electro-optical imaging systems. ICIP 2009: 3789-3792 - [c29]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: 72540L - 2008
- [j20]David G. Stork:
Book Review: "complexity Management in Fuzzy Systems: a Rule Base Compression Approach", Alexander Gegov. Int. J. Comput. Intell. Appl. 7(1): 101-102 (2008) - 2007
- [j19]David G. Stork, Marco F. Duarte
Computer Vision, Image Analysis, and Master Art: Part 3. IEEE Multim. 14(1): 14-18 (2007) - [j18]David G. Stork, Marco F. Duarte
Revisiting Computer Image Analysis and Art. IEEE Multim. 14(3): 108-109 (2007) - 2006
- [j17]David G. Stork:
Computer Vision, Image Analysis, and Master Art: Part 1. IEEE Multim. 13(3): 16-20 (2006) - [j16]David G. Stork, Micah K. Johnson:
Computer Vision, Image Analysis, and Master Art: Part 2. IEEE Multim. 13(4): 12-17 (2006) - [c28]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: 255-258 - 2005
- [c27]Chuck P. Lam, David G. Stork:
Toward Optimal Labeling Strategy under Multiple Unreliable Labelers. AAAI Spring Symposium: Knowledge Collection from Volunteer Contributors 2005: 42-47 - [c26]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 - [c25]David G. Stork:
Asymmetry in Lotto carpets and its implication for Hockney's optical projection theory. Human Vision and Electronic Imaging 2005: 337-343 - 2004
- [c24]David G. Stork:
Did Jan van Eyck build the first photocopier in 1432? Color Imaging: Processing, Hardcopy, and Applications 2004: 50-56 - [c23]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: 645-648 - 2003
- [c22]Rob J. van Glabbeek, David G. Stork:
Query Nets: Interacting Workflow Modules That Ensure Global Termination. Business Process Management 2003: 184-199 - [c21]Chuck P. Lam, David G. Stork:
Evaluating Classifiers by Means of Test Data with Noisy Labels. IJCAI 2003: 513-518 - [c20]David G. Stork:
Illumination and Color in the Hockney Theory of Renaissance Painting Praxis: A Critical Evaluation. CIC 2003: 11-15 - 2002
- [c19]David G. Stork, Rob J. van Glabbeek:
Token-Controlled Place Refinement in Hierarchical Petri Nets with Application to Active Document Workflow. ICATPN 2002: 394-413 - 2001
- [b1]Richard O. Duda, Peter E. Hart, David G. Stork:
Pattern classification, 2nd Edition. Wiley 2001, ISBN 9780471056690, pp. I-XX, 1-654 - [c18]David G. Stork:
Toward a Computational Theory of Data Acquisition and Truthing. COLT/EuroCOLT 2001: 194-207 - [c17]David G. Stork:
An Architecture Supporting the Collection and Monitoring of Data Openly Contributed over the World Wide Web. WETICE 2001: 380-385 - [c16]David G. Stork:
Keynote address: the HAL 9000 computer and the vision of 2001: a space odyssey. WSC 2001: 3 - 2000
- [j15]Ziming Liu, David G. Stork:
Is paperless really more? Commun. ACM 43(11): 94-97 (2000) - [j14]David G. Stork:
Using Open Data Collection for Intelligent Software. Computer 33(10): 104-106 (2000) - [c15]Maya R. Gupta, Michael J. Gormish, David G. Stork:
Block Color Quantization: A New Method for Color Halftoning. ICIP 2000: 460-463
1990 – 1999
- 1999
- [j13]Marti A. Hearst, Robin D. Hunson, David G. Stork:
Building intelligent systems one e-citizen at a time. IEEE Intell. Syst. 14(3): 16-20 (1999) - [c14]David G. Stork:
Character and Document Research in the Open Mind Initiative. ICDAR 1999: 1-12 - 1998
- [j12]David G. Stork:
Generic object recognition using form and function - By louise stark and kevin bowyer. World scientic, 1996. Pattern Anal. Appl. 1(2): 144 (1998) - [c13]David G. Stork:
From HAL to Office Appliances: Human-machine Interfaces in Science Fiction and Reality. IUI 1998: 181 - 1997
- [j11]David G. Stork:
Happy Birthday, HAL! Computer 30(1): 24-25 (1997) - 1996
- [j10]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): 263-272 (1996) - [c12]David G. Stork, Marcus E. Hennecke:
Invited Speech: "Speechreading: An Overview of Image Processing, Feature Extraction, Sensory Intergration and Pattern Recognition Techiques. FG 1996: 2-3 - 1995
- [c11]Ahmad Zandi, David G. Stork, James D. Allen:
Optimizing bit-plane context-dependent entropy coding for palettized images. ICIP 1995: 270-273 - 1994
- [j9]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): 257-258 (1994) - [c10]Alessandro Sperduti, David G. Stork:
A Rapid Graph-based Method for Arbitrary Transformation-Invariant Pattern Classification. NIPS 1994: 665-672 - 1993
- [j8]David G. Stork, James D. Allen:
How to solve the N-bit encoder problem with just one hidden unit. Neurocomputing 5(2): 141-143 (1993) - [j7]David G. Stork:
Letter to the editor. Neural Networks 6(5): 609 (1993) - [c9]Babak Hassibi, David G. Stork, Gregory J. Wolff:
Optimal Brain Surgeon and general network pruning. ICNN 1993: 293-299 - [c8]Babak Hassibi, David G. Stork, Gregory J. Wolff:
Optimal Brain Surgeon: Extensions and performance comparison. NIPS 1993: 263-270 - [c7]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: 896-903 - [c6]Gregory J. Wolff, K. Venkatesh Prasad, David G. Stork, Marcus E. Hennecke:
Lipreading by Neural Networks: Visual Preprocessing, Learning, and Sensory Integration. NIPS 1993: 1027-1034 - 1992
- [j6]Igor Grebert, David G. Stork, Ron Keesing, Steve Mims:
Connectionist generalization for production: An example from GridFont. Neural Networks 5(4): 699-710 (1992) - [j5]David G. Stork, James D. Allen:
How to solve the N-bit parity problem with two hidden units. Neural Networks 5(6): 923-926 (1992) - [c5]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: 206-217 - [c4]Babak Hassibi, David G. Stork:
Second Order Derivatives for Network Pruning: Optimal Brain Surgeon. NIPS 1992: 164-171 - 1991
- [j4]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): 157-158 (1991) - [j3]David G. Stork:
Sources of Neural Structure in Speech and Language Processing. Int. J. Neural Syst. 2(3): 159-167 (1991) - [j2]David G. Stork:
Book Review: "Evolution of the First Nervous Systems", Peter A. V. Anderson (ed.). Int. J. Neural Syst. 2(4): 363-365 (1991) - [c3]Ron Keesing, David G. Stork, Carla J. Shatz:
Retinogeniculate Development: The Role of Competition and Correlated Retinal Activity. NIPS 1991: 91-97 - [c2]Igor Grebert, David G. Stork, Ron Keesing, Steve Mims:
Network Generalization for Production: Learning and Producing Styled Letterforms. NIPS 1991: 1118-1124 - 1990
- [j1]David G. Stork:
Book Review: "Artificial Neural Systems: Foundations, Paradigms, Applications, and Implementations", Patrick K. Simpson. Int. J. Neural Syst. 1(3): 285-259 (1990) - [c1]Ron Keesing, David G. Stork:
Evolution and Learning in Neural Networks. NIPS 1990: 804-810
Coauthor Index
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last updated on 2024-09-20 00:39 CEST by the dblp team
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