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10 results on '"Ross, Kevin W."'

1. Effect of Graft Attachment Status and Intraocular Pressure on Descemet Stripping Automated Endothelial Keratoplasty Outcomes in the Cornea Preservation Time Study

Author

Aldave, Anthony J., Terry, Mark A., Szczotka-Flynn, Loretta B., Liang, Wendi, Ayala, Allison R., Maguire, Maureen G., O'Brien, Robert C., Benetz, Beth Ann, Bokosky, John E., Dunn, Steven P., Gillette, Thomas E., Hammersmith, Kristin M., Hardten, David R., Jeng, Bennie H., Jones, Marc F., Lindstrom, Richard L., Maverick, Kenneth J., Nirankari, Verinder S., Oliva, Matthew S., Raber, Irving M., Rapuano, Christopher J., Rosenwasser, George O.D., Ross, Kevin W., Seedor, John W., Shamie, Neda, Stoeger, Christopher G., Tauber, Shachar, Van Meter, Woodford S., Verdier, David D., and Lass, Jonathan H.

Published
2019
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2. Prelamellar Dissection Donor Corneal Thickness Is Associated With Descemet Stripping Automated Endothelial Keratoplasty Operative Complications in the Cornea Preservation Time Study

Author

Ross, Kevin W., Stoeger, Christopher G., Rosenwasser, George O. D., OʼBrien, Robert C., Szczotka-Flynn, Loretta B., Ayala, Allison R., Maguire, Maureen G., Benetz, Beth Ann, Dahl, Patricia, Drury, Donna C., Dunn, Steven P., Farazdaghi, Sameera M., Hoover, Caroline K., Macsai, Marian S., Mian, Shahzad I., Nordlund, Michael L., Penta, Jeffrey G., Soper, Mark C., Terry, Mark A., Verdier, David D., Williams, Doyce V., and Lass, Jonathan H.

Published
2019
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3. Effect of Cornea Preservation Time on Success of Descemet Stripping Automated Endothelial Keratoplasty: A Randomized Clinical Trial

Author

Rosenwasser, George O., Szczotka-Flynn, Loretta B., Ayala, Allison R., Liang, Wendi, Aldave, Anthony J., Dunn, Steven P., McCall, Tyrone, Navarro, Lisa C., Pramanik, Sudeep, Ross, Kevin W., Stulting, R. Doyle, Terry, Mark A., Tu, Elmer Y., Verdier, David D., Kollman, Craig, Gal, Robin L., Beck, Roy W., and Lass, Jonathan H.

Published
2017
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4. Corneal Endothelial Cell Loss 3 Years After Successful Descemet Stripping Automated Endothelial Keratoplasty in the Cornea Preservation Time Study: A Randomized Clinical Trial

Author

Lass, Jonathan H., Benetz, Beth Ann, Verdier, David D., Szczotka-Flynn, Loretta B., Ayala, Allison R., Liang, Wendi, Aldave, Anthony J., Dunn, Steven P., McCall, Tyrone, Mian, Shahzad I., Navarro, Lisa C., Patel, Sanjay V., Pramanik, Sudeep, Rosenwasser, George O., Ross, Kevin W., Terry, Mark A., Kollman, Craig, Gal, Robin L., and Beck, Roy W.

Published
2017
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8. Cornea Preservation Time Study

Author

Lass, Jonathan H., primary, Szczotka-Flynn, Loretta B., additional, Ayala, Allison R., additional, Benetz, Beth A., additional, Gal, Robin L., additional, Aldave, Anthony J., additional, Corrigan, Michelle M., additional, Dunn, Steven P., additional, McCall, Ty L., additional, Pramanik, Sudeep, additional, Rosenwasser, George O., additional, Ross, Kevin W., additional, Terry, Mark A., additional, and Verdier, David D., additional

Published
2015
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10. A Genetic Adaptive System for Image Understanding and Learning Research. Phase 1

Author

INSTITUTE FOR THE STUDY OF INTELLIGENT SYSTEMS ANN ARBOR MI, Douthat, Dean Z., Ross, Kevin W., INSTITUTE FOR THE STUDY OF INTELLIGENT SYSTEMS ANN ARBOR MI, Douthat, Dean Z., and Ross, Kevin W.

Abstract

This report documents the efforts and results of initial phase research on machine learning directed at application for real time machine vision and automatic target recognition. The particular paradigm pursued is based on genetic algorithms and classifiers modeled on the summation of Mendelian genetic recombination, Darwinian selection and ecological notions of competition. This machine learning approach is strongly supported by sound statistical theory. A second thread of research was the development of massively parallel computing hardware based on the Geometric/Arithmetic Parallel Processor (GAPP). This machine has a large number of processors, each one bit wide with a full Arithmetic/Logic Unit (full adder) and with local memory per processor. The basic research hypothesis of the subject effort has been that GAPP contained sufficient hardware capability to provide a substrate for a Classifier and Genetic Algorithm system. The goal has been demonstrated by constructing and running the necessary software on the GAPP, its controller and its host. The resulting fusion of software and hardware is called a Genetic Algorithm/ Classifier Engine (GACE) in the same sense as a LISP engine or a database engine. The resulting quantum jump in performance should open doors both to application and to more interesting and relevant research. (SDW), Original contains color plates: All DTIC and NTIS reproductions will be in black and white.

Published
1989

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