Jack Sklansky

Publication Activity (10 Years)

Years Active: 1960-2002
Publications (10 Years): 0

Publications

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. Medical Imaging: Image Processing (2002)
Brian Lofy, Jack Sklansky
Segmenting multisensor aerial images in class-scale space. Pattern Recognit. 34 (9) (2001)
Mineichi Kudo, Jack Sklansky
Comparison of algorithms that select features for pattern classifiers. Pattern Recognit. 33 (1) (2000)
Mineichi Kudo, Petr Somol, Pavel Pudil, Masaru Shimbo, Jack Sklansky
Comparison of Classifier-Specific Feature Selection Algorithms. SSPR/SPR (2000)
Eric Y. Tao, Chester J. Ornes, Jack Sklansky
Automatic detection of microcalcifications in digital mammography. Medical Imaging: Image Processing (1998)
Chester Ornes, Anthony Disher, Jack Sklansky
A visual neural network that learns perceptual relationships. ICPR (1998)
Mineichi Kudo, Jack Sklansky
A comparative evaluation of medium- and large-scale feature selectors for pattern classifiers. Kybernetika 34 (4) (1998)
Chester Ornes, Jack Sklansky
A visual neural classifier. IEEE Trans. Syst. Man Cybern. Part B 28 (4) (1998)
Mineichi Kudo, Jack Sklansky
Classifier-Independent Feature Selection For Two-Stage Feature Selection. SSPR/SPR (1998)
Jack Sklansky, Eric Y. Tao, Chester Ornes, Anthony Disher
A Neurodatabase System for Mammographic Screening. CBMS (1998)
Chester Ornes, Jack Sklansky
A visual multi-expert neural classifier. ICNN (1997)
Chester Ornes, Jack Sklansky
A neural network that explains as well as predicts financial market behavior. CIFEr (1997)
Chester Ornes, Jack Sklansky
A neural network that visualizes what it classifies. Pattern Recognit. Lett. 18 (11-13) (1997)
Eric Y. Tao, Jack Sklansky
Analysis of mammograms aided by database of images of calcifications and textures. Medical Imaging: Image Processing (1996)
Bing-Bing Chai, Xinhua Zhuang, Yunxin Zhao, Jack Sklansky
Binary linear decision tree with genetic algorithm. ICPR (1996)
Mark Vriesenga, Jack Sklansky
Neural modeling of piecewise linear classifiers. ICPR (1996)
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) (1996)
Jack Sklansky, Mark Vriesenga
Genetic Selection and Neural Modeling of Piecewise-Linear Classifiers. Int. J. Pattern Recognit. Artif. Intell. 10 (5) (1996)
Mark Vriesenga, Glenn Healey, Jack Sklansky, Kalman Peleg
Colored Illumination for Enhancing Discriminability in Machine Vision. J. Vis. Commun. Image Represent. 6 (3) (1995)
Leon Bobrowski, Jack Sklansky
Linear classifiers by window training. IEEE Trans. Syst. Man Cybern. 25 (1) (1995)
Thinh V. Nguyen, Jack Sklansky
Reconstructing the 3-D medial axes of coronary arteries in single-view cineangiograms. IEEE Trans. Medical Imaging 13 (1) (1994)
Leon Bobrowski, Jack Sklansky
Linear classifiers by window training and basis exchange. ICPR (2) (1994)
Jordi Ribas-Corbera, Jack Sklansky
Interframe Interpolation of Cinematic Sequences. J. Vis. Commun. Image Represent. 4 (4) (1993)
Satoshi Suzuki, Naonori Ueda, Jack Sklansky
Graph-Based Thinning for Binary Images. Int. J. Pattern Recognit. Artif. Intell. 7 (5) (1993)
R. Agarwal, Jack Sklansky
Estimating Optical Flow for Large Interframe Displacements. CAIP (1993)
Satoshi Suzuki, Jack Sklansky
Extracting nonrigid moving objects by temporal edges. ICPR (1) (1992)
Jordi Ribas-Corbera, Jack Sklansky
Interpolation of cinematic sequences. WACV (1992)
Luong Van Tran, Robert C. Bahn, Jack Sklansky
Reconstructing the cross sections of coronary arteries from biplane angiograms. IEEE Trans. Medical Imaging 11 (4) (1992)
Luong Van Tran, Jack Sklansky
Flexible mask subtraction for digital angiography. IEEE Trans. Medical Imaging 11 (3) (1992)
R. Agarwal, Jack Sklansky
Estimating optical flow from clustered trajectories in velocity-time. ICPR (1) (1992)
Mark Vriesenga, Glenn Healey, Kalman Peleg, Jack Sklansky
Controlling illumination color to enhance object discriminability. CVPR (1992)
Ruye Wang, Jack Sklansky
Multiresolution method for reconstructing the cross sections of coronary arteries from biplane angiograms. ICPR (3) (1992)
Dan Gutfinger, Jack Sklansky
Robust Classifiers by Mixed Adaptation. IEEE Trans. Pattern Anal. Mach. Intell. 13 (6) (1991)
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) (1991)
Youngtae Park, Jack Sklansky
Automated design of linear tree classifiers. Pattern Recognit. 23 (12) (1990)
Youngtae Park, Jack Sklansky
Fast tree classifiers. ICPR (1) (1990)
Dan Gutfinger, R. Nishimura, H. Doi, Jack Sklansky
Robust curve detection by temporal geodesics. ICCV (1990)
Wojciech W. Siedlecki, Jack Sklansky
A note on genetic algorithms for large-scale feature selection. Pattern Recognit. Lett. 10 (5) (1989)
Wojciech W. Siedlecki, Jack Sklansky
Constrained Genetic Optimization via Dynarnic Reward-Penalty Balancing and Its Use in Pattern Recognition. ICGA (1989)
Wojciech W. Siedlecki, Kinga Siedlecka, Jack Sklansky
An overview of mapping techniques for exploratory pattern analysis. Pattern Recognit. 21 (5) (1988)
Wojciech W. Siedlecki, Kinga Siedlecka, Jack Sklansky
Experiments on mapping techniques for exploratory pattern analysis. Pattern Recognit. 21 (5) (1988)
Ramesh C. Jain, André Oosterlinck, Jorge Sanz, Jack Sklansky, Masahiko Yachida
An editorial welcome. Mach. Vis. Appl. 1 (1) (1988)
Wojciech W. Siedlecki, Jack Sklansky
On Automatic Feature Selection. Int. J. Pattern Recognit. Artif. Intell. 2 (2) (1988)
Youngtae Park, Jack Sklansky
Automated design of piecewise-linear classifiers of multiple-class data. ICPR (1988)
Iman Foroutan, Jack Sklansky
Feature Selection for Automatic Classification of Non-Gaussian Data. IEEE Trans. Syst. Man Cybern. 17 (2) (1987)
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) (1987)
Manabu Ichino, Jack Sklansky
The relative neighborhood graph for mixed feature variables. Pattern Recognit. 18 (2) (1985)
Leonard A. Ferrari, Jack Sklansky
A note on duhamel integrals and running average filters. Comput. Vis. Graph. Image Process. 29 (3) (1985)
Leonard A. Ferrari, P. V. Sankar, Jack Sklansky
Minimal rectangular partitions of digitized blobs. Comput. Vis. Graph. Image Process. 28 (1) (1984)
Manabu Ichino, Jack Sklansky
Optimum feature selection by zero-one integer programming. IEEE Trans. Syst. Man Cybern. 14 (5) (1984)
Leonard A. Ferrari, Jack Sklansky
A fast recursive algorithm for binary-valued two-dimensional filters. Comput. Vis. Graph. Image Process. 26 (3) (1984)
Leonard A. Ferrari, Jack Sklansky
A fast recursive algorithm for binary valued two-dimensional filters. Comput. Vis. Graph. Image Process. 22 (2) (1983)
Chul E. Kim, Jack Sklansky
Digital and cellular convexity. Pattern Recognit. 15 (5) (1982)
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) (1982)
Jack Sklansky
Finding the convex hull of a simple polygon. Pattern Recognit. Lett. 1 (2) (1982)
Lewis G. Minor, Jack Sklansky
The Detection and Segmentation of Blobs in Infrared Images. IEEE Trans. Syst. Man Cybern. 11 (3) (1981)
Jack Sklansky, Leo Michelotti
Locally Trained Piecewise Linear Classifiers. IEEE Trans. Pattern Anal. Mach. Intell. 2 (2) (1980)
Jack Sklansky, Víctor M. González
Fast polygonal approximation of digitized curves. Pattern Recognit. 12 (5) (1980)
Jack Sklansky
On the Hough Technique for Curve Detection. IEEE Trans. Computers 27 (10) (1978)
Jack Sklansky
Image Segmentation and Feature Extraction. IEEE Trans. Syst. Man Cybern. 8 (4) (1978)
Harry Wechsler, Jack Sklansky
Finding the rib cage in chest radiographs. Pattern Recognit. 9 (1) (1977)
Dana H. Ballard, Jack Sklansky
A Ladder-Structured Decision Tree for Recognizing Tumors in Chest Radiographs. IEEE Trans. Computers 25 (5) (1976)
Jack Sklansky, Luigi P. Cordella, Stefano Levialdi
Parallel Detection of Concavities in Cellular Blobs. IEEE Trans. Computers 25 (2) (1976)
Jack Sklansky, Dennis F. Kibler
A Theory of Nonuniformly Digitized Binary Pictures. IEEE Trans. Syst. Man Cybern. 6 (9) (1976)
Caolyn Kimme, Dana Balard, Jack Sklansky
Finding Circles by an Array of Accumulators. Commun. ACM 18 (2) (1975)
Harry Wechsler, Jack Sklansky
Automatic Detection Of Rib Contours in Chest Radiographs. IJCAI (1975)
Jack Sklansky, Philemon M. Merryman
A Continuous Two-Dimensional Model of Threshold Learning. IEEE Trans. Syst. Man Cybern. 3 (1) (1973)
Jack Sklansky, Robert L. Chazin, Bruce J. Hansen
Minimum-Perimeter Polygons of Digitized Silhouettes. IEEE Trans. Computers 21 (3) (1972)
Jack Sklansky, Paul J. Nahin
A Parallel Mechanism for Describing Silhouettes. IEEE Trans. Computers 21 (11) (1972)
Jack Sklansky
Measuring Concavity on a Rectangular Mosaic. IEEE Trans. Computers 21 (12) (1972)
Gustav N. Wassel, Jack Sklansky
Training a One-Dimensional Classifier to Minimize the Probability of Error. IEEE Trans. Syst. Man Cybern. 2 (4) (1972)
Neil J. Bershad, Jack Sklansky
Threshold learning and Brownian motion (Corresp.). IEEE Trans. Inf. Theory 17 (3) (1971)
Jack Sklansky, P. J. Najin
A Parallel Mechanism for Recognizing Silhouettes. IFIP Congress (1) (1971)
Jack Sklansky
R70-16 Unate Cellular Logic. IEEE Trans. Computers 19 (6) (1970)
Jack Sklansky
Recognition of convex blobs. Pattern Recognit. 2 (1) (1970)
Jack Sklansky
Thresholded Convolutions Operations. J. ACM 17 (1) (1970)
Jack Sklansky, Neil J. Bershad
The Dynamics of Time-Varying Threshold Learning Inf. Control. 15 (6) (1969)
Jack Sklansky
Recognizing Convex Blobs. IJCAI (1969)
Jack Sklansky, M. Finkelstein
A Formalism for Program Translation. J. ACM 15 (2) (1968)
Jack Sklansky, A. J. Korenjak, H. S. Stone
Canonical Tributary Networks. IEEE Trans. Electron. Comput. 14 (6) (1965)
Jack Sklansky
Threshold training of two-mode signal detection. IEEE Trans. Inf. Theory 11 (3) (1965)
Jack Sklansky
Ultimate-Speed Adders. IEEE Trans. Electron. Comput. 12 (2) (1963)
Jack Sklansky
General Synthesis of Tributary Switching Networks. IEEE Trans. Electron. Comput. 12 (5) (1963)
Jack Sklansky, Kenneth R. Kaplan
Transients in Markov Chains. IEEE Trans. Electron. Comput. 12 (6) (1963)
Jack Sklansky
An Evaluation of Several Two-Summand Binary Adders. IRE Trans. Electron. Comput. 9 (2) (1960)
Jack Sklansky
Conditional-Sum Addition Logic. IRE Trans. Electron. Comput. 9 (2) (1960)