Dr. Ravishankar Rao Profile

Dr. Ravishankar Rao

Research Staff Member at IBM Thomas J Watson Research Ctr

SPIE Involvement:

Author

Publications (19)

Proceedings Article | 24 February 2012 Paper

ADHD classification using bag of words approach on network features

Berkan Solmaz, Soumyabrata Dey, A. Ravishankar Rao, Mubarak Shah

Proceedings Volume 8314, 83144T (2012) https://doi.org/10.1117/12.911598

KEYWORDS: Brain, Functional magnetic resonance imaging, Neuroimaging, Brain mapping, Receivers, Statistical analysis, Quantization, Magnetic resonance imaging, Diagnostics, Image processing

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Proceedings Article | 15 March 2011 Paper

Fast computation of functional networks from fMRI activity: a multi-platform comparison

A. Ravishankar Rao, Rajesh Bordawekar, Guillermo Cecchi

Proceedings Volume 7962, 79624L (2011) https://doi.org/10.1117/12.878368

KEYWORDS: Functional magnetic resonance imaging, Network security, Brain, Image analysis, Statistical analysis, Analytical research, Medical imaging, Neuroimaging, Scanners, Visualization

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Proceedings Article | 4 March 2011 Paper

Characteristics of voxel prediction power in full-brain Granger causality analysis of fMRI data

Rahul Garg, Guillermo Cecchi, A. Ravishankar Rao

Proceedings Volume 7965, 796502 (2011) https://doi.org/10.1117/12.878311

KEYWORDS: Brain, Data modeling, Functional magnetic resonance imaging, Stochastic processes, Brain mapping, Machine learning, Analytical research, Neuroimaging, Matrices, Visualization

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Proceedings Article | 3 March 2011 Paper

Accelerating statistical image reconstruction algorithms for fan-beam x-ray CT using cloud computing

Somesh Srivastava, A. Ravishankar Rao, Vadim Sheinin

Proceedings Volume 7961, 796134 (2011) https://doi.org/10.1117/12.877877

KEYWORDS: Clouds, Projection systems, Reconstruction algorithms, X-ray computed tomography, Image restoration, Sodium, X-ray imaging, X-rays, Scanners, Internet

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Proceedings Article | 13 February 2008 Paper

Statistics of natural scenes and the cortical representation of color

G. Cecchi, A. Rao, Y. Xiao, E. Kaplan

Proceedings Volume 6806, 680607 (2008) https://doi.org/10.1117/12.769003

KEYWORDS: Visualization, Visual cortex, Statistical analysis, Spatial frequencies, Image filtering, Neurons, Optical recording, Databases, Data processing, Brain mapping

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Proceedings Article | 16 February 2006 Paper

Translation invariance in a network of oscillatory units

A. Ravishankar Rao, Guillermo Cecchi, Charles Peck, James Kozloski

Proceedings Volume 6064, 60641I (2006) https://doi.org/10.1117/12.648229

KEYWORDS: Visual system, Visualization, Neurons, Deconvolution, Oscillators, Image segmentation, Neural networks, Machine learning, Chemical elements, Superposition

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One of the important features of the human visual system is that it is able to recognize objects in a scale and translational invariant manner. However, achieving this desirable behavior through biologically realistic networks is a challenge. The synchronization of neuronal firing patterns has been suggested as a possible solution to the binding problem (where a biological mechanism is sought to explain how features that represent an object can be scattered across a network, and yet be unified). This observation has led to neurons being modeled as oscillatory dynamical units. It is possible for a network of these dynamical units to exhibit synchronized oscillations under the right conditions. These network models have been applied to solve signal deconvolution or blind source separation problems. However, the use of the same network to achieve properties that the visual sytem exhibits, such as scale and translational invariance have not been fully explored. Some approaches investigated in the literature (Wallis, 1996) involve the use of non-oscillatory elements that are arranged in a hierarchy of layers. The objects presented are allowed to move, and the network utilizes a trace learning rule, where a time averaged output value is used to perform Hebbian learning with respect to the input value. This is a modification of the standard Hebbian learning rule, which typically uses instantaneous values of the input and output. In this paper we present a network of oscillatory amplitude-phase units connected in two layers. The types of connections include feedforward, feedback and lateral. The network consists of amplitude-phase units that can exhibit synchronized oscillations. We have previously shown that such a network can segment the components of each input object that most contribute to its classification. Learning is unsupervised and based on a Hebbian update, and the architecture is very simple. We extend the ability of this network to address the problem of translational invariance. We show that by adopting a specific treatment of the phase values of the output layer, the network exhibits translational invariant object representation. The scheme used in training is as follows. The network is presented with an input, which then moves. During the motion the amplitude and phase of the upper layer units is not reset, but continues with the past value before the introduction of the object in the new position. Only the input layer is changed instantaneously to reflect the moving object. The network behavior is such that it categorizes the translated objects with the same label as the stationary object, thus establishing an invariant categorization with respect to translation. This is a promising result as it uses the same framework of oscillatory units that achieves synchrony, and introduces motion to achieve translational invariance.

Proceedings Article | 9 February 2006 Paper

Inference and segmentation in cortical processing

Yuan Liu, Guillermo Cecchi, A. Ravishankar Rao, James Kozloski, Charles Peck

Proceedings Volume 6057, 60570Y (2006) https://doi.org/10.1117/12.650804

KEYWORDS: Neural networks, Superposition, Deconvolution, Network architectures, Neurons, Visual process modeling, Evolutionary algorithms, Machine learning, Brain, Visual cortex

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Proceedings Article | 18 March 2005 Paper

A model of the formation of a self-organized cortical representation of color

A. Ravishankar Rao, Guillermo Cecchi, Charles Peck, James Kozloski

Proceedings Volume 5666, (2005) https://doi.org/10.1117/12.585526

KEYWORDS: RGB color model, Cones, Brain mapping, Visualization, Data processing, Retina, Neurons, Signal processing, Spatial filters, Data modeling

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Proceedings Article | 28 December 2001 Paper

Color document analysis

Chung-Hui Kuo, A. Ravishankar Rao, Gerry Thompson

Proceedings Volume 4663, (2001) https://doi.org/10.1117/12.452976

KEYWORDS: Image segmentation, Optical filters, Image filtering, Binary data, Image processing, Image compression, Visualization, RGB color model, Detection and tracking algorithms, Image processing algorithms and systems

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Proceedings Article | 21 December 2000 Paper

Color halftone descreening based on color sigma filters

Chung-Hui Kuo, A. Ravishankar Rao, Gerry Thompson

Proceedings Volume 4300, (2000) https://doi.org/10.1117/12.410811

KEYWORDS: Halftones, Optical filters, Image filtering, Image processing, Linear filtering, Finite impulse response filters, RGB color model, Moire patterns, Image processing algorithms and systems, Digital filtering

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Proceedings Article | 24 May 1999 Paper

Digital stereoscopic imaging

A. Ravishankar Rao, Alejandro Jaimes

Proceedings Volume 3639, (1999) https://doi.org/10.1117/12.349375

KEYWORDS: Digital cameras, Cameras, Photography, Stereoscopy, Image resolution, Image quality, Scanners, Imaging systems, Computing systems, Color reproduction

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Proceedings Article | 22 December 1998 Paper

Segmentation and automatic descreening of scanned documents

Alejandro Jaimes, Frederick Mintzer, A. Ravishankar Rao, Gerry Thompson

Proceedings Volume 3648, (1998) https://doi.org/10.1117/12.334597

KEYWORDS: Image segmentation, Halftones, Printing, Moire patterns, Digital libraries, Linear filtering, Image processing, Detection and tracking algorithms, Electrical engineering, Photography

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Proceedings Article | 1 April 1998 Paper

Automatic visible watermarking of images

A. Ravishankar Rao, Gordon Braudaway, Frederick Mintzer

Proceedings Volume 3314, (1998) https://doi.org/10.1117/12.304677

KEYWORDS: Digital watermarking, RGB color model, Statistical modeling, Human subjects, Digital libraries, Photography, Illumination engineering, Visual process modeling, Visual analytics, Visualization

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Proceedings Article | 13 March 1996 Paper

Relationship between texture terms and texture images: a study in human texture perception

A. Ravishankar Rao, Nalini Bhushan, Gerald Lohse

Proceedings Volume 2670, (1996) https://doi.org/10.1117/12.234797

KEYWORDS: Visualization, Volume rendering, Databases, Associative arrays, Matrices, Human subjects, Distributed interactive simulations, Image retrieval, Human-machine interfaces, Roads

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Proceedings Article | 11 March 1996 Paper

Synthesis of fine grain YAG:RE3+ phosphors for low-voltage display devices

Ravi Rao

Proceedings Volume 2651, (1996) https://doi.org/10.1117/12.235348

KEYWORDS: Yttrium, Sol-gels, Thulium, YAG lasers, Particles, Ion exchange, Scanning electron microscopy, Luminescence, Field emission displays, Europium

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Proceedings Article | 6 May 1993 Paper

Automatic defect classification for integrated circuits

Paul Chou, A. Ravishankar Rao, Martin Sturzenbecker, Virginia Brecher

Proceedings Volume 1907, (1993) https://doi.org/10.1117/12.144802

KEYWORDS: Classification systems, Defect detection, Image classification, Inspection, Process control, Scene classification, Integrated circuits, Machine vision, Manufacturing, Scanning electron microscopy

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Proceedings Article | 27 August 1992 Paper

Identifying high-level features of texture perception

A. Ravishankar Rao, Gerald Lohse

Proceedings Volume 1666, (1992) https://doi.org/10.1117/12.135988

KEYWORDS: Visualization, Human vision and color perception, Image classification, Analytical research, Machine vision, Computer vision technology, Taxonomy, Feature extraction, Fractal analysis, Image segmentation

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Proceedings Article | 1 March 1992 Paper

Fast confocal image processing for inspection

A. Ravishankar Rao, Frederick Wu, Jon Mandeville, Pieter Kerstens

Proceedings Volume 1708, (1992) https://doi.org/10.1117/12.58562

KEYWORDS: Confocal microscopy, Deconvolution, Inspection, Image processing, Evolutionary algorithms, Signal detection, Electronic filtering, Signal processing, Microscopes, Machine vision

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Proceedings Article | 1 June 1990 Paper

Quantitative measures for surface texture description in semiconductor wafer inspection

A. Ravishankar Rao, Ramesh Jain

Proceedings Volume 1261, (1990) https://doi.org/10.1117/12.20043

KEYWORDS: Inspection, Semiconducting wafers, Image segmentation, Fractal analysis, Differential equations, Wafer inspection, Evolutionary algorithms, Coherence (optics), Image processing, Algorithm development

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