default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDJack Sklansky
Person information
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
2000 – 2009
- 2002
[c25]Yuan Xu, Scott C. Neu, Chester J. Ornes, Janis F. Owens, Jack Sklansky, Daniel J. Valentino:
Optimization of active-contour model parameters using genetic algorithms: segmentation of breast lesions in mammograms. Image Processing 2002- 2001
- [j61]Brian Lofy, Jack Sklansky:
Segmenting multisensor aerial images in class-scale space. Pattern Recognit. 34(9): 1825-1839 (2001) - 2000
- [j60]Mineichi Kudo
, Jack Sklansky:
Comparison of algorithms that select features for pattern classifiers. Pattern Recognit. 33(1): 25-41 (2000) - [c24]Mineichi Kudo, Petr Somol, Pavel Pudil, Masaru Shimbo, Jack Sklansky:
Comparison of Classifier-Specific Feature Selection Algorithms. SSPR/SPR 2000: 677-686
1990 – 1999
- 1998
- [j59]Mineichi Kudo, Jack Sklansky:
A comparative evaluation of medium- and large-scale feature selectors for pattern classifiers. Kybernetika 34(4): 429-434 (1998) - [j58]Chester Ornes, Jack Sklansky:
A visual neural classifier. IEEE Trans. Syst. Man Cybern. Part B 28(4): 620-625 (1998) - [c23]Jack Sklansky, Eric Y. Tao, Chester Ornes, Anthony Disher:
A Neurodatabase System for Mammographic Screening. CBMS 1998: 78-83 - [c22]Chester Ornes, Anthony Disher, Jack Sklansky:
A visual neural network that learns perceptual relationships. ICPR 1998: 873-875 - [c21]Eric Y. Tao, Chester J. Ornes, Jack Sklansky:
Automatic detection of microcalcifications in digital mammography. Image Processing 1998 - [c20]Mineichi Kudo, Jack Sklansky:
Classifier-Independent Feature Selection For Two-Stage Feature Selection. SSPR/SPR 1998: 548-554 - 1997
- [j57]Chester Ornes, Jack Sklansky:
A neural network that visualizes what it classifies. Pattern Recognit. Lett. 18(11-13): 1301-1306 (1997) - [c19]Chester Ornes, Jack Sklansky:
A neural network that explains as well as predicts financial market behavior. CIFEr 1997: 43-49 - [c18]Chester Ornes, Jack Sklansky:
A visual multi-expert neural classifier. ICNN 1997: 1448-1453 - 1996
- [j56]Jack Sklansky, Mark Vriesenga:
Genetic Selection and Neural Modeling of Piecewise-Linear Classifiers. Int. J. Pattern Recognit. Artif. Intell. 10(5): 587-612 (1996) - [j55]Bing-Bing Chai, Tong Huang, Xinhua Zhuang, Yunxin Zhao, Jack Sklansky:
Piecewise linear classifiers using binary tree structure and genetic algorithm. Pattern Recognit. 29(11): 1905-1917 (1996) - [c17]Mark Vriesenga, Jack Sklansky:
Neural modeling of piecewise linear classifiers. ICPR 1996: 281-285 - [c16]Bing-Bing Chai, Xinhua Zhuang, Yunxin Zhao, Jack Sklansky:
Binary linear decision tree with genetic algorithm. ICPR 1996: 530-534 - [c15]Eric Y. Tao, Jack Sklansky:
Analysis of mammograms aided by database of images of calcifications and textures. Image Processing 1996 - 1995
- [j54]Mark Vriesenga, Glenn Healey, Jack Sklansky, Kalman Peleg:
Colored Illumination for Enhancing Discriminability in Machine Vision. J. Vis. Commun. Image Represent. 6(3): 244-255 (1995) - [j53]Leon Bobrowski, Jack Sklansky:
Linear classifiers by window training. IEEE Trans. Syst. Man Cybern. 25(1): 1-9 (1995) - 1994
- [j52]Thinh V. Nguyen, Jack Sklansky:
Reconstructing the 3-D medial axes of coronary arteries in single-view cineangiograms. IEEE Trans. Medical Imaging 13(1): 61-73 (1994) - [c14]Leon Bobrowski, Jack Sklansky:
Linear classifiers by window training and basis exchange. ICPR (2) 1994: 513-514 - 1993
- [j51]Satoshi Suzuki, Naonori Ueda, Jack Sklansky:
Graph-Based Thinning for Binary Images. Int. J. Pattern Recognit. Artif. Intell. 7(5): 1009-1030 (1993) - [j50]Jordi Ribas-Corbera, Jack Sklansky:
Interframe Interpolation of Cinematic Sequences. J. Vis. Commun. Image Represent. 4(4): 392-406 (1993) - [c13]R. Agarwal, Jack Sklansky:
Estimating Optical Flow for Large Interframe Displacements. CAIP 1993: 403-411 - [p4]Jack Sklansky, Wojciech W. Siedlecki:
Large-Scale Feature Selection. Handbook of Pattern Recognition and Computer Vision 1993: 61-62 - [p3]Wojciech W. Siedlecki, Jack Sklansky:
On Automatic Feature Selection. Handbook of Pattern Recognition and Computer Vision 1993: 63-87 - [p2]Wojciech W. Siedlecki, Jack Sklansky:
A note on Genetic Algorithms for Large-Scale Feature Selection. Handbook of Pattern Recognition and Computer Vision 1993: 88-107 - [p1]Wojciech W. Siedlecki, Jack Sklansky:
Constrained Genetic Optimization via Dynamic Reward-penalty Balancing and its Use in Pattern Recognition. Handbook of Pattern Recognition and Computer Vision 1993: 108-123 - 1992
- [j49]Luong Van Tran, Jack Sklansky:
Flexible mask subtraction for digital angiography. IEEE Trans. Medical Imaging 11(3): 407-415 (1992) - [j48]Luong Van Tran, Robert C. Bahn, Jack Sklansky:
Reconstructing the cross sections of coronary arteries from biplane angiograms. IEEE Trans. Medical Imaging 11(4): 517-529 (1992) - [c12]Mark Vriesenga, Glenn Healey, Kalman Peleg, Jack Sklansky:
Controlling illumination color to enhance object discriminability. CVPR 1992: 710-712 - [c11]Satoshi Suzuki, Jack Sklansky:
Extracting nonrigid moving objects by temporal edges. ICPR (1) 1992: 69-73 - [c10]R. Agarwal, Jack Sklansky:
Estimating optical flow from clustered trajectories in velocity-time. ICPR (1) 1992: 215-219 - [c9]Ruye Wang, Jack Sklansky:
Multiresolution method for reconstructing the cross sections of coronary arteries from biplane angiograms. ICPR (3) 1992: 667-670 - [c8]Jordi Ribas-Corbera, Jack Sklansky:
Interpolation of cinematic sequences. WACV 1992: 36-44 - 1991
- [j47]Dragutin Petkovic, J. Wilder, Masakazu Ejiri, Robert M. Haralick, Ramesh C. Jain, Peter A. Ruetz, Jack Sklansky, C. W. Swonger:
Machine vision in the 1990s: Applications and how to get there. Mach. Vis. Appl. 4(2): 113-126 (1991) - [j46]Dan Gutfinger, Jack Sklansky:
Robust Classifiers by Mixed Adaptation. IEEE Trans. Pattern Anal. Mach. Intell. 13(6): 552-567 (1991) - 1990
- [j45]Youngtae Park, Jack Sklansky:
Automated design of linear tree classifiers. Pattern Recognit. 23(12): 1393-1412 (1990) - [c7]Dan Gutfinger, R. Nishimura, H. Doi, Jack Sklansky:
Robust curve detection by temporal geodesics. ICCV 1990: 752-756 - [c6]Youngtae Park, Jack Sklansky:
Fast tree classifiers. ICPR (1) 1990: 684-686
1980 – 1989
- 1989
- [j44]Wojciech W. Siedlecki, Jack Sklansky:
A note on genetic algorithms for large-scale feature selection. Pattern Recognit. Lett. 10(5): 335-347 (1989) - [c5]Wojciech W. Siedlecki, Jack Sklansky:
Constrained Genetic Optimization via Dynarnic Reward-Penalty Balancing and Its Use in Pattern Recognition. ICGA 1989: 141-150 - 1988
- [j43]Wojciech W. Siedlecki, Jack Sklansky:
On Automatic Feature Selection. Int. J. Pattern Recognit. Artif. Intell. 2(2): 197-220 (1988) - [j42]Ramesh C. Jain, André Oosterlinck, Jorge Sanz, Jack Sklansky, Masahiko Yachida:
An editorial welcome. Mach. Vis. Appl. 1(1): 1 (1988) - [j41]Wojciech W. Siedlecki, Kinga Siedlecka, Jack Sklansky:
An overview of mapping techniques for exploratory pattern analysis. Pattern Recognit. 21(5): 411-429 (1988) - [j40]Wojciech W. Siedlecki, Kinga Siedlecka, Jack Sklansky:
Experiments on mapping techniques for exploratory pattern analysis. Pattern Recognit. 21(5): 431-438 (1988) - [c4]Youngtae Park, Jack Sklansky:
Automated design of piecewise-linear classifiers of multiple-class data. ICPR 1988: 1068-1071 - 1987
- [j39]Leonard A. Ferrari, P. V. Sankar, S. Shinnaka, Jack Sklansky:
Recursive Algorithms for Implementing Digital Image Filters. IEEE Trans. Pattern Anal. Mach. Intell. 9(3): 461-466 (1987) - [j38]Iman Foroutan, Jack Sklansky:
Feature Selection for Automatic Classification of Non-Gaussian Data. IEEE Trans. Syst. Man Cybern. 17(2): 187-198 (1987) - 1985
- [j37]Leonard A. Ferrari, Jack Sklansky:
A note on duhamel integrals and running average filters. Comput. Vis. Graph. Image Process. 29(3): 358-360 (1985) - [j36]Manabu Ichino, Jack Sklansky:
The relative neighborhood graph for mixed feature variables. Pattern Recognit. 18(2): 161-167 (1985) - 1984
- [j35]Leonard A. Ferrari, Jack Sklansky:
A fast recursive algorithm for binary-valued two-dimensional filters. Comput. Vis. Graph. Image Process. 26(3): 292-302 (1984) - [j34]Leonard A. Ferrari, P. V. Sankar, Jack Sklansky:
Minimal rectangular partitions of digitized blobs. Comput. Vis. Graph. Image Process. 28(1): 58-71 (1984) - [j33]Manabu Ichino, Jack Sklansky:
Optimum feature selection by zero-one integer programming. IEEE Trans. Syst. Man Cybern. 14(5): 737-746 (1984) - 1983
- [j32]Leonard A. Ferrari, Jack Sklansky:
A fast recursive algorithm for binary valued two-dimensional filters. Comput. Vis. Graph. Image Process. 22(2): 310 (1983) - 1982
- [j31]Pathamadi V. Sankar, Jack Sklansky:
A Gestalt-Guided Heuristic Boundary Follower for X-Ray Images of Lung Nodules. IEEE Trans. Pattern Anal. Mach. Intell. 4(3): 326-331 (1982) - [j30]Chul E. Kim, Jack Sklansky:
Digital and cellular convexity. Pattern Recognit. 15(5): 359-367 (1982) - [j29]Jack Sklansky:
Finding the convex hull of a simple polygon. Pattern Recognit. Lett. 1(2): 79-83 (1982) - 1981
- [j28]Lewis G. Minor, Jack Sklansky:
The Detection and Segmentation of Blobs in Infrared Images. IEEE Trans. Syst. Man Cybern. 11(3): 194-201 (1981) - 1980
- [j27]Jack Sklansky, Leo Michelotti:
Locally Trained Piecewise Linear Classifiers. IEEE Trans. Pattern Anal. Mach. Intell. 2(2): 101-111 (1980) - [j26]Jack Sklansky, Víctor M. González:
Fast polygonal approximation of digitized curves. Pattern Recognit. 12(5): 327-331 (1980)
1970 – 1979
- 1978
- [j25]Jack Sklansky:
On the Hough Technique for Curve Detection. IEEE Trans. Computers 27(10): 923-926 (1978) - [j24]Jack Sklansky:
Image Segmentation and Feature Extraction. IEEE Trans. Syst. Man Cybern. 8(4): 237-247 (1978) - 1977
- [j23]Harry Wechsler, Jack Sklansky:
Finding the rib cage in chest radiographs. Pattern Recognit. 9(1): 21-30 (1977) - 1976
- [j22]Jack Sklansky, Luigi P. Cordella, Stefano Levialdi:
Parallel Detection of Concavities in Cellular Blobs. IEEE Trans. Computers 25(2): 187-196 (1976) - [j21]Dana H. Ballard, Jack Sklansky:
A Ladder-Structured Decision Tree for Recognizing Tumors in Chest Radiographs. IEEE Trans. Computers 25(5): 503-513 (1976) - [j20]Jack Sklansky, Dennis F. Kibler:
A Theory of Nonuniformly Digitized Binary Pictures. IEEE Trans. Syst. Man Cybern. 6(9): 637-647 (1976) - 1975
- [j19]Caolyn Kimme, Dana Balard, Jack Sklansky:
Finding Circles by an Array of Accumulators. Commun. ACM 18(2): 120-122 (1975) - [c3]Harry Wechsler, Jack Sklansky:
Automatic Detection Of Rib Contours in Chest Radiographs. IJCAI 1975: 688-694 - 1973
- [j18]Jack Sklansky, Philemon M. Merryman:
A Continuous Two-Dimensional Model of Threshold Learning. IEEE Trans. Syst. Man Cybern. 3(1): 51-61 (1973) - 1972
- [j17]Jack Sklansky, Robert L. Chazin, Bruce J. Hansen:
Minimum-Perimeter Polygons of Digitized Silhouettes. IEEE Trans. Computers 21(3): 260-268 (1972) - [j16]Jack Sklansky, Paul J. Nahin:
A Parallel Mechanism for Describing Silhouettes. IEEE Trans. Computers 21(11): 1233-1239 (1972) - [j15]Jack Sklansky:
Measuring Concavity on a Rectangular Mosaic. IEEE Trans. Computers 21(12): 1355-1364 (1972) - [j14]Gustav N. Wassel, Jack Sklansky:
Training a One-Dimensional Classifier to Minimize the Probability of Error. IEEE Trans. Syst. Man Cybern. 2(4): 533-541 (1972) - 1971
- [j13]Neil J. Bershad, Jack Sklansky:
Threshold learning and Brownian motion (Corresp.). IEEE Trans. Inf. Theory 17(3): 350-352 (1971) - [c2]Jack Sklansky, P. J. Najin:
A Parallel Mechanism for Recognizing Silhouettes. IFIP Congress (1) 1971: 224-228 - 1970
- [j12]Jack Sklansky:
Thresholded Convolutions Operations. J. ACM 17(1): 161-165 (1970) - [j11]Jack Sklansky:
Recognition of convex blobs. Pattern Recognit. 2(1): 3-10 (1970) - [j10]Jack Sklansky:
R70-16 Unate Cellular Logic. IEEE Trans. Computers 19(6): 566 (1970)
1960 – 1969
- 1969
- [j9]Jack Sklansky, Neil J. Bershad:
The Dynamics of Time-Varying Threshold Learning. Inf. Control. 15(6): 455-486 (1969) - [c1]Jack Sklansky:
Recognizing Convex Blobs. IJCAI 1969: 107-116 - 1968
- [j8]Jack Sklansky, M. Finkelstein:
A Formalism for Program Translation. J. ACM 15(2): 165-175 (1968) - 1965
- [j7]Jack Sklansky, A. J. Korenjak, H. S. Stone:
Canonical Tributary Networks. IEEE Trans. Electron. Comput. 14(6): 961-963 (1965) - [j6]Jack Sklansky:
Threshold training of two-mode signal detection. IEEE Trans. Inf. Theory 11(3): 353-362 (1965) - 1963
- [j5]Jack Sklansky:
Ultimate-Speed Adders. IEEE Trans. Electron. Comput. 12(2): 142-148 (1963) - [j4]Jack Sklansky:
General Synthesis of Tributary Switching Networks. IEEE Trans. Electron. Comput. 12(5): 464-469 (1963) - [j3]Jack Sklansky, Kenneth R. Kaplan:
Transients in Markov Chains. IEEE Trans. Electron. Comput. 12(6): 921-922 (1963) - 1960
- [j2]Jack Sklansky:
An Evaluation of Several Two-Summand Binary Adders. IRE Trans. Electron. Comput. 9(2): 213-226 (1960) - [j1]Jack Sklansky:
Conditional-Sum Addition Logic. IRE Trans. Electron. Comput. 9(2): 226-231 (1960)
Coauthor Index
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from 
to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the 
of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2025-01-21 00:22 CET by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
