Se invita a la comunidad universitaria a la charla detallada a continuación, a
ser dictada por el Prof. Rama Chellappa, de la Universidad de Maryland, EEUU,
en el marco del Proyecto Basal AC3E:
-Título: "Deep Learning Networks for Computer Vision: Blessing or Curse?"
-Fecha y hora: Viernes 11 de diciembre, 14:00 hrs
-Lugar: Auditorio Guillermo Feick, B-221, Departamento de Electrónica
-Expositor: Rama Chellappa, Chair, Department of Electrical and Computer
Engineering University of Maryland
https://www.umiacs.umd.edu/people/rama
ABSTRACT
Over the last five years so, deep learning networks have shown that impressive results can be obtained for several computer vision problems such as face detection, object detection/recognition and face verification. In an ongoing effort on face verification, we have been able to improve performance using deep learning networks, which is both exhilarating and worrisome. While performance improvement using deep learning networks should be seen as a blessing (who can argue against performance), several problems remain to be addressed. For example, reliance on the availability of very large annotated data set may be a handicap. Being able to generalize networks across test data with different distributions (domain adaptation) as well as different problems is also important. Deriving bounds on the number of training sam! ples, gi ven the distance between training and test data distributions will be useful for planning data acquisition/annotation tasks. We will address some of these issues in the talk.
BIO:
Prof. Rama Chellappa received the B.E. (Hons.) degree in Electronics and
Communication Engineering from the University of Madras, India and the M.E.
(with Distinction) degree from the Indian Institute of Science, Bangalore,
India. He received the M.S.E.E. and Ph.D. Degrees in Electrical Engineering
from Purdue University, West Lafayette, IN. During 1981-1991, he was a
faculty member in the department of EE-Systems at University of Southern
California (USC). Since 1991, he has been a Professor of Electrical and
Computer Engineering (ECE) and an affiliate Professor of Computer Science
at University of Maryland (UMD), College Park. He is also affiliated with
the Center for Automation Research and the Institute for Advanced Computer
Studies (Permanent Member) and is serving as the Chair of the ECE
department. In 2005, he was named a Minta Martin Professor of Engineering.
His current research interests span many areas in image processing,
computer vision and pattern recognition. Prof. Chellappa is a recipient of
an NSF Presidential Young Investigator Award and four IBM Faculty
Development Awards. He received two paper awards and the K.S. Fu Prize from
the International Association of Pattern Recognition (IAPR). He is a
recipient of the Society, Technical Achievement and Meritorious Service
Awards from the IEEE Signal Processing Society. He also received the
Technical Achievement and Meritorious Service Awards from the IEEE Computer
Society. He is a recipient of Excellence in teaching award from the School
of Engineering at USC. At UMD, he received college and university level
recognitions for research, teaching, innovation and mentoring undergraduate
students. In 2010, he was recognized as an Outstanding ECE by Purdue
University. Prof. Chellappa served as the Editor-in-Chief of IEEE
Transactions on Pattern Analysis and Machine Intelligence and as the
General and Technical Program Chair/Co-Chair for several IEEE international
and national conferences and workshops. He is a Golden Core Member of the
IEEE Computer Society, served as a Distinguished Lecturer of the IEEE
Signal Processing Society and as the President of IEEE Biometrics Council.
He is a Fellow of IEEE, IAPR, OSA, AAAS, ACM, AAAI and holds four patents.
Publicado en: Charlas
