*Sklain, C.[Cheryl]*
**Co Author Listing** * Multilevel Vision Based Spatial Reasoning for Robotic Tasks

*Sklair, C.*
**Co Author Listing** * Employing Sensor Repositioning to Refine Spatial Reasoning in an Industrial Robotic Environment

*Sklair, C.W.*
**Co Author Listing** * Perspective View of Three Points, The

*Sklansky, J.[Jack]*
**Co Author Listing** * Automated design of linear tree classifiers

* Automated design of piecewise-linear classifiers of multiple-class data

* Automatic Detection of Rib Contours in Chest Radiographs

* Biomedical Image Analysis

* Biplane analysis of atheromatous coronary arteries

* Colored Illumination for Enhancing Discriminability in Machine Vision

* Comparison of algorithms that select features for pattern classifiers

* Controlling Illumination color to Enhance Object Discriminability

* Detecting the Edges of Lung Tumors by Classification Techniques

* Detection and Segmentation of Blobs in Infrared Images, The

* Digital and Cellular Convexity

* Edge Detection by Estimation of Multiple-Order Derivatives

* Efficient Two-Dimensional Filters Using B-Spline Functions

* Estimating optical flow for large interframe displacements

* Estimating Optical Flow from Clustered Trajectories in Velocity-Time

* Experiments on Mapping Techniques for Exploratory Pattern Analysis

* Extracting Nonrigid Moving Objects By Temporal Edges

* Fast polygonal approximation of digitized curves

* Fast Recursive Algorithm for Binary-Valued Two-Dimensional Filters, A

* Fast tree classifiers

* Finding Circles by an Array of Accumulators

* Finding the Convex Hull of a Simple Polygon

* Finding the Rib Cage in Chest Radiographs

* Gestalt-Guided Boundary Follower for X-Ray Images of Lung Nodules, A

* Graph-Based Thinning for Binary Images

* Image Segmentation and Feature Extraction

* Interpolation of cinematic sequences

* Ladder-Structured Decision Tree for Recognizing Tumors in Chest Radiographs, A

* Large-Scale Feature Selection

* Linear classifiers by window training and basis exchange

* Markov Random Field Models of Digitized Image Texture

* Markov Random Fields as Models of Digitized Image Texture

* Measuring Concavity on a Rectangular Mosaic

* Minimal Rectangular Partitions of Digitized Blobs

* Minimum Perimeter Polygons of Digitized Silhouettes

* Multiple-Order Derivatives for Detecting Local Image Characteristics

* Multiresolution method for reconstructing the cross sections of coronary arteries from biplane angiograms

* Neural Modeling of Piecewise Linear Classifiers

* Neural-Network That Visualizes What It Classifies, A

* Note on Duhamel Integrals and Running Average Filters, A

* Note on Genetic Algorithms for Large-Scale Feature Selection, A

* On Automatic Feature Selection

* On Filling Cellular Concavities

* On the Hough Technique for Curve Detection

* Overview of Mapping Techniques for Exploratory Pattern Analysis, An

* Parallel Detection of Concavities in Cellular Blobs

* Parallel Mechanism for Describing Silhouettes, A

* Piecewise Linear Detection of Boundaries in Chest Radiographs

* Piecewise-Linear Classifiers Using Binary-Tree Structure and Genetic Algorithm

* Recognition of Convex Blobs

* Reconstructing a Network of Three-Dimensional Curves from a Small Number of Projections

* Recursive Algorithms for Implementing Digital Image Filters

* relative neighborhood graph for mixed feature variables, The

* Robust classifiers by mixed adaptation

* Robust Curve Detection by Temporal Geodesics

* Segmentation of People in Motion

* Segmenting multisensor aerial images in class-scale space

* Skeleton Generation from x,y Boundary Sequences

* Skeletons from Sequential Boundary Data

* Theory of Nonuniformly Digitized Binary Pictures, A

* Thresholded Convolutions Operations

* Use of Markov Random Fields as Models of Texture, The

* Visual Neural Classifier, A

* Visual Neural Network that Learns Perceptual Relationships, A

Includes: Sklansky, J.[Jack] Sklansky, J.

64 for Sklansky, J.

Last update:13-Jul-24 15:45:53

Use price@usc.edu for comments.