An Evaluation of Several Two-Summand Binary Adders. - Jack Sklansky (IRE Trans. Electron. Comput., 1960)

Conditional-Sum Addition Logic. - Jack Sklansky (IRE Trans. Electron. Comput., 1960)

Ultimate-Speed Adders. - Jack Sklansky (IEEE Trans. Electron. Comput., 1963)

General Synthesis of Tributary Switching Networks. - Jack Sklansky (IEEE Trans. Electron. Comput., 1963)

Transients in Markov Chains. - Jack Sklansky; Kenneth R. Kaplan (IEEE Trans. Electron. Comput., 1963)

Canonical Tributary Networks. - Jack Sklansky; A. J. Korenjak; H. S. Stone (IEEE Trans. Electron. Comput., 1965)

Threshold training of two-mode signal detection. - Jack Sklansky (IEEE Trans. Inf. Theory, 1965)

A Formalism for Program Translation. - Jack Sklansky; M. Finkelstein (J. ACM, 1968)

Recognizing Convex Blobs. - Jack Sklansky (IJCAI, 1969)

The Dynamics of Time-Varying Threshold Learning - Jack Sklansky; Neil J. Bershad (Inf. Control., 1969)

Thresholded Convolutions Operations. - Jack Sklansky (J. ACM, 1970)

Recognition of convex blobs. - Jack Sklansky (Pattern Recognit., 1970)

R70-16 Unate Cellular Logic. - Jack Sklansky (IEEE Trans. Computers, 1970)

A Parallel Mechanism for Recognizing Silhouettes. - Jack Sklansky; P. J. Najin (IFIP Congress (1), 1971)

Threshold learning and Brownian motion (Corresp.). - Neil J. Bershad; Jack Sklansky (IEEE Trans. Inf. Theory, 1971)

Measuring Concavity on a Rectangular Mosaic. - Jack Sklansky (IEEE Trans. Computers, 1972)

Minimum-Perimeter Polygons of Digitized Silhouettes. - Jack Sklansky; Robert L. Chazin; Bruce J. Hansen (IEEE Trans. Computers, 1972)

A Parallel Mechanism for Describing Silhouettes. - Jack Sklansky; Paul J. Nahin (IEEE Trans. Computers, 1972)

Training a One-Dimensional Classifier to Minimize the Probability of Error. - Gustav N. Wassel; Jack Sklansky (IEEE Trans. Syst. Man Cybern., 1972)

A Continuous Two-Dimensional Model of Threshold Learning. - Jack Sklansky; Philemon M. Merryman (IEEE Trans. Syst. Man Cybern., 1973)

Automatic Detection Of Rib Contours in Chest Radiographs. - Harry Wechsler; Jack Sklansky (IJCAI, 1975)

Finding Circles by an Array of Accumulators. - Caolyn Kimme; Dana Balard; Jack Sklansky (Commun. ACM, 1975)

A Ladder-Structured Decision Tree for Recognizing Tumors in Chest Radiographs. - Dana H. Ballard; Jack Sklansky (IEEE Trans. Computers, 1976)

Parallel Detection of Concavities in Cellular Blobs. - Jack Sklansky; Luigi P. Cordella; Stefano Levialdi (IEEE Trans. Computers, 1976)

A Theory of Nonuniformly Digitized Binary Pictures. - Jack Sklansky; Dennis F. Kibler (IEEE Trans. Syst. Man Cybern., 1976)

Finding the rib cage in chest radiographs. - Harry Wechsler; Jack Sklansky (Pattern Recognit., 1977)

On the Hough Technique for Curve Detection. - Jack Sklansky (IEEE Trans. Computers, 1978)

Image Segmentation and Feature Extraction. - Jack Sklansky (IEEE Trans. Syst. Man Cybern., 1978)

Locally Trained Piecewise Linear Classifiers. - Jack Sklansky; Leo Michelotti (IEEE Trans. Pattern Anal. Mach. Intell., 1980)

Fast polygonal approximation of digitized curves. - Jack Sklansky; Víctor M. González 001 (Pattern Recognit., 1980)

The Detection and Segmentation of Blobs in Infrared Images. - Lewis G. Minor; Jack Sklansky (IEEE Trans. Syst. Man Cybern., 1981)

A Gestalt-Guided Heuristic Boundary Follower for X-Ray Images of Lung Nodules. - Pathamadi V. Sankar; Jack Sklansky (IEEE Trans. Pattern Anal. Mach. Intell., 1982)

Digital and cellular convexity. - Chul E. Kim; Jack Sklansky (Pattern Recognit., 1982)

Finding the convex hull of a simple polygon. - Jack Sklansky (Pattern Recognit. Lett., 1982)

A fast recursive algorithm for binary valued two-dimensional filters. - Leonard A. Ferrari; Jack Sklansky (Comput. Vis. Graph. Image Process., 1983)

Minimal rectangular partitions of digitized blobs. - Leonard A. Ferrari; P. V. Sankar; Jack Sklansky (Comput. Vis. Graph. Image Process., 1984)

Optimum feature selection by zero-one integer programming. - Manabu Ichino; Jack Sklansky (IEEE Trans. Syst. Man Cybern., 1984)

A note on duhamel integrals and running average filters. - Leonard A. Ferrari; Jack Sklansky (Comput. Vis. Graph. Image Process., 1985)

The relative neighborhood graph for mixed feature variables. - Manabu Ichino; Jack Sklansky (Pattern Recognit., 1985)

Recursive Algorithms for Implementing Digital Image Filters. - Leonard A. Ferrari; P. V. Sankar; S. Shinnaka; Jack Sklansky (IEEE Trans. Pattern Anal. Mach. Intell., 1987)

Feature Selection for Automatic Classification of Non-Gaussian Data. - Iman Foroutan; Jack Sklansky (IEEE Trans. Syst. Man Cybern., 1987)

Automated design of piecewise-linear classifiers of multiple-class data. - Youngtae Park; Jack Sklansky (ICPR, 1988)

On Automatic Feature Selection. - Wojciech W. Siedlecki; Jack Sklansky (Int. J. Pattern Recognit. Artif. Intell., 1988)

An editorial welcome. - Ramesh C. Jain; André Oosterlinck; Jorge Sanz; Jack Sklansky; Masahiko Yachida (Mach. Vis. Appl., 1988)

An overview of mapping techniques for exploratory pattern analysis. - Wojciech W. Siedlecki; Kinga Siedlecka; Jack Sklansky (Pattern Recognit., 1988)

Experiments on mapping techniques for exploratory pattern analysis. - Wojciech W. Siedlecki; Kinga Siedlecka; Jack Sklansky (Pattern Recognit., 1988)

Constrained Genetic Optimization via Dynarnic Reward-Penalty Balancing and Its Use in Pattern Recognition. - Wojciech W. Siedlecki; Jack Sklansky (ICGA, 1989)

A note on genetic algorithms for large-scale feature selection. - Wojciech W. Siedlecki; Jack Sklansky (Pattern Recognit. Lett., 1989)

Robust curve detection by temporal geodesics. - Dan Gutfinger; R. Nishimura; H. Doi; Jack Sklansky (ICCV, 1990)

Fast tree classifiers. - Youngtae Park; Jack Sklansky (ICPR (1), 1990)

Automated design of linear tree classifiers. - Youngtae Park; Jack Sklansky (Pattern Recognit., 1990)

Machine vision in the 1990s: Applications and how to get there. - Dragutin Petkovic; J. Wilder; Masakazu Ejiri; Robert M. Haralick; Ramesh C. Jain; Peter A. Ruetz; Jack Sklansky; C. W. Swonger (Mach. Vis. Appl., 1991)

Robust Classifiers by Mixed Adaptation. - Dan Gutfinger; Jack Sklansky (IEEE Trans. Pattern Anal. Mach. Intell., 1991)

Controlling illumination color to enhance object discriminability. - Mark Vriesenga; Glenn Healey; Kalman Peleg; Jack Sklansky (CVPR, 1992)

Estimating optical flow from clustered trajectories in velocity-time. - R. Agarwal; Jack Sklansky (ICPR (1), 1992)

Extracting nonrigid moving objects by temporal edges. - Satoshi Suzuki; Jack Sklansky (ICPR (1), 1992)

Multiresolution method for reconstructing the cross sections of coronary arteries from biplane angiograms. - Ruye Wang; Jack Sklansky (ICPR (3), 1992)

Interpolation of cinematic sequences. - Jordi Ribas-Corbera; Jack Sklansky (WACV, 1992)

Reconstructing the cross sections of coronary arteries from biplane angiograms. - Luong Van Tran; Robert C. Bahn; Jack Sklansky (IEEE Trans. Medical Imaging, 1992)

Flexible mask subtraction for digital angiography. - Luong Van Tran; Jack Sklansky (IEEE Trans. Medical Imaging, 1992)

On Automatic Feature Selection. - Wojciech W. Siedlecki; Jack Sklansky (Handbook of Pattern Recognition and Computer Vision, 1993)

A note on Genetic Algorithms for Large-Scale Feature Selection. - Wojciech W. Siedlecki; Jack Sklansky (Handbook of Pattern Recognition and Computer Vision, 1993)

Constrained Genetic Optimization via Dynamic Reward-penalty Balancing and its Use in Pattern Recognition. - Wojciech W. Siedlecki; Jack Sklansky (Handbook of Pattern Recognition and Computer Vision, 1993)

Large-Scale Feature Selection. - Jack Sklansky; Wojciech W. Siedlecki (Handbook of Pattern Recognition and Computer Vision, 1993)

Estimating Optical Flow for Large Interframe Displacements. - R. Agarwal; Jack Sklansky (CAIP, 1993)

Graph-Based Thinning for Binary Images. - Satoshi Suzuki; Naonori Ueda; Jack Sklansky (Int. J. Pattern Recognit. Artif. Intell., 1993)

Interframe Interpolation of Cinematic Sequences. - Jordi Ribas-Corbera; Jack Sklansky (J. Vis. Commun. Image Represent., 1993)

Linear classifiers by window training and basis exchange. - Leon Bobrowski; Jack Sklansky (ICPR (2), 1994)

Reconstructing the 3-D medial axes of coronary arteries in single-view cineangiograms. - Thinh V. Nguyen; Jack Sklansky (IEEE Trans. Medical Imaging, 1994)

Colored Illumination for Enhancing Discriminability in Machine Vision. - Mark Vriesenga; Glenn Healey; Jack Sklansky; Kalman Peleg (J. Vis. Commun. Image Represent., 1995)

Linear classifiers by window training. - Leon Bobrowski; Jack Sklansky (IEEE Trans. Syst. Man Cybern., 1995)

Binary linear decision tree with genetic algorithm. - Bing-Bing Chai; Xinhua Zhuang; Yunxin Zhao; Jack Sklansky (ICPR, 1996)

Neural modeling of piecewise linear classifiers. - Mark Vriesenga; Jack Sklansky (ICPR, 1996)

Analysis of mammograms aided by database of images of calcifications and textures. - Eric Y. Tao; Jack Sklansky (Image Processing, 1996)

Genetic Selection and Neural Modeling of Piecewise-Linear Classifiers. - Jack Sklansky; Mark Vriesenga (Int. J. Pattern Recognit. Artif. Intell., 1996)

Piecewise linear classifiers using binary tree structure and genetic algorithm. - Bing-Bing Chai; Tong Huang; Xinhua Zhuang; Yunxin Zhao; Jack Sklansky (Pattern Recognit., 1996)

A neural network that explains as well as predicts financial market behavior. - Chester Ornes; Jack Sklansky (CIFEr, 1997)

A visual multi-expert neural classifier. - Chester Ornes; Jack Sklansky (ICNN, 1997)

A neural network that visualizes what it classifies. - Chester Ornes; Jack Sklansky (Pattern Recognit. Lett., 1997)

A Neurodatabase System for Mammographic Screening. - Jack Sklansky; Eric Y. Tao; Chester Ornes; Anthony Disher (CBMS, 1998)

A visual neural network that learns perceptual relationships. - Chester Ornes; Anthony Disher; Jack Sklansky (ICPR, 1998)

Automatic detection of microcalcifications in digital mammography. - Eric Y. Tao; Chester J. Ornes; Jack Sklansky (Image Processing, 1998)

Classifier-Independent Feature Selection For Two-Stage Feature Selection. - Mineichi Kudo; Jack Sklansky (SSPR/SPR, 1998)

A comparative evaluation of medium- and large-scale feature selectors for pattern classifiers. - Mineichi Kudo; Jack Sklansky (Kybernetika, 1998)

A visual neural classifier. - Chester Ornes; Jack Sklansky (IEEE Trans. Syst. Man Cybern. Part B, 1998)

Comparison of Classifier-Specific Feature Selection Algorithms. - Mineichi Kudo; Petr Somol; Pavel Pudil; Masaru Shimbo; Jack Sklansky (SSPR/SPR, 2000)

Comparison of algorithms that select features for pattern classifiers. - Mineichi Kudo; Jack Sklansky (Pattern Recognit., 2000)

Segmenting multisensor aerial images in class-scale space. - Brian Lofy; Jack Sklansky (Pattern Recognit., 2001)

Optimization of active-contour model parameters using genetic algorithms: segmentation of breast lesions in mammograms. - Yuan Xu; Scott C. Neu; Chester J. Ornes; Janis F. Owens; Jack Sklansky; Daniel J. Valentino (Image Processing, 2002)