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Akhileswar Ganesh Vaidyanathan

Researcher at DuPont

Publications -  14
Citations -  424

Akhileswar Ganesh Vaidyanathan is an academic researcher from DuPont. The author has contributed to research in topics: Object Attribute & Kernel (image processing). The author has an hindex of 9, co-authored 14 publications receiving 424 citations.

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Patent

Distributed hierarchical evolutionary modeling and visualization of empirical data

TL;DR: A distributed hierarchical evolutionary modeling and visualization of empirical data method and machine readable storage medium for creating an empirical modeling system based upon previously acquired data is presented in this article, where the data represents inputs to the systems and corresponding outputs from the system.
Patent

Adaptive display system

TL;DR: In this article, a digital image analysis method for automatically identifying an object in a background, characterizing the object by color by determining at least one interior point of the object, and displaying the object on a monitor in color corresponding to the natural color of the objects was presented.
Patent

Iterative method and system of identifying valid objects in a background of an image

TL;DR: In this article, an entropic kernel is used to recursively analyze the gray level space for candidate objects and validating the presence of valid objects by comparing the candidate object attribute values to a defined set of valid object attributes contained in a driver.
Patent

Adaptive vision system

TL;DR: In this article, an entropic kernel is used to recursively analyze the gray level space for candidate objects and validating the presence of valid objects by comparing the candidate object attribute values to a defined set of valid object attributes contained in a driver.
Patent

Methods for determining the exterior points of an object in a background

TL;DR: In this article, two general methods can be used to access the local exterior environment of an object, knowing the perimeter points of the object, and a known exterior shape, such as a circle, is used to characterize the exterior contour region.