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Workshop overview

Great advances have been made in the acquisition of image data, from conventional photography, CT scanning, and satellite imaging to thenow ubiquitous digital cameras embedded in cell phones and other wireless devices. Although the semantic understanding of the shapesand other objects appearing in images is effortless for human beings, the corresponding problem in machine perception - namely, automaticinterpretation via computer programs - remains a major open challenge in modern science. In fact, there are very few systems whose valuederives from the analysis rather than collection of image data, and this "semantic gap" impedes scientific and technological advances inmany areas, including automated medical diagnosis, robotics, industrial automation, and effective security and surveillance.In this CSLS Workshop, three distinguished experts in the field of Computational Vision and Image Analysis share their thoughts on thecurrent state of the art and future directions in the field.

Remark: This workshop was held on October 30, 2003 as part of the Computational Sciences Lecture Series (CSLS) at the University of Wisconsin-Madison.

Hierarchical designs for pattern recognition

By Prof. Donald Geman (Dept. of Applied Mathematics and Statistics and Center for Imaging Science,Johns Hopkins University, USA)

Slides of talk [PDF] (Not yet available.) | Video [WMV] | Video [MPG]

ABSTRACT: It is unlikely that complex problems in machine perception, such as scene interpretation, will yield directly to improved methodsof statistical learning. Some organizational framework is needed to confront the small amount of data relative to the large number ofpossible explanations, and to make sure that intensive computation is restricted to genuinely ambiguous regions. As an example, I willpresent a "twenty questions" approach to pattern recognition. The object of analysis is the computational process itself rather thanprobability distributions (Bayesian inference) or decision boundaries (statistical learning). Under mild assumptions, optimal strategiesexhibit a steady progression from broad scope coupled with low power to high power coupled with dedication to specificexplanations. Several theoretical results will be mentioned (joint work with Gilles Blanchard) as well as experiments in object detection(joint work with Yali Amit and Francois Fleuret).

Modeling and inference of dynamic visual processes

By Prof. Stefano Soatto (Department of Computer Science, University of California Los Angeles,USA)

Slides of talk [PDF] (Not yet available.) | Video [WMV]

ABSTRACT: "We see in order to move, and we move in order to see." Inthis expository talk, I will explore the role of vision as a sensor for interaction with physical space. Since the complexity of thephysical world is far superior to that of its measured images, inferring a generic representation of the scene is an intrinsicallyill-posed problem. However, the task becomes well-posed within the context of a specific control task. I will display recent results inthe inference of dynamical models of visual scenes for the purpose of motion control, shape visualization, rendering, and classification.

Computational anatomy and models for image analysis

By Prof. Michael Miller (Director of the Center for Imaging Science, The Seder Professor of Biomedical Engineering,Professor of Electrical and Computer Engineering, Johns Hopkins University,USA)

Slides of talk [PDF] (Not yet available.) | Video [WMV]

ABSTRACT: University Recent years have seen rapid advances in the mathematical specification of models for image analysis of humananatomy. As first described in "Computational Anatomy: An Emerging Discipline" (Grenander and Miller, Quarterly of Applied Mathematics,Vol. 56, 617-694, 1998), human anatomy is modelled as a deformable template, an orbit under the group action of infinite dimensionaldiffeomorphisms. In this talk, we will describe recent advances in CA,specifying a metric on the ensemble of images, and examine distances between elements of the orbits, "Group Actions, Homeomorphisms, andMatching: A General Framework" (Miller and Younes, Int. J. Comp. Vision Vol. 41, 61-84, 2001), "On the Metrics ofEuler-Lagrange Equations of Computational Anatomy (Annu. Rev. Biomed. Eng., Vol. 4, 375-405, 2002). Numerous resultswill be shown comparing shapes through this metric formulation of the deformable template, including results from disease testing on thehippocampus, and cortical structural and functional mapping.

Questions & Answers

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Sanket Reply
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Damian Reply
types of nano material
abeetha Reply
I start with an easy one. carbon nanotubes woven into a long filament like a string
many many of nanotubes
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I'm interested in nanotube
what is nanomaterials​ and their applications of sensors.
Ramkumar Reply
what is nano technology
Sravani Reply
what is system testing?
preparation of nanomaterial
Victor Reply
Yes, Nanotechnology has a very fast field of applications and their is always something new to do with it...
Himanshu Reply
good afternoon madam
what is system testing
what is the application of nanotechnology?
In this morden time nanotechnology used in many field . 1-Electronics-manufacturad IC ,RAM,MRAM,solar panel etc 2-Helth and Medical-Nanomedicine,Drug Dilivery for cancer treatment etc 3- Atomobile -MEMS, Coating on car etc. and may other field for details you can check at Google
anybody can imagine what will be happen after 100 years from now in nano tech world
after 100 year this will be not nanotechnology maybe this technology name will be change . maybe aftet 100 year . we work on electron lable practically about its properties and behaviour by the different instruments
name doesn't matter , whatever it will be change... I'm taking about effect on circumstances of the microscopic world
how hard could it be to apply nanotechnology against viral infections such HIV or Ebola?
silver nanoparticles could handle the job?
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I'm interested in Nanotube
this technology will not going on for the long time , so I'm thinking about femtotechnology 10^-15
can nanotechnology change the direction of the face of the world
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