Larry Hall, "Transfer Learning Using Deep Features for Medical Imaging Analysis"
Join the Notre Dame Institute for Advanced Study on Thursday, November 10, 2016 at 4:00 p.m. in 123 Nieuwland Science Hall for "Transfer Learning Using Deep Features for Medical Imaging Analysis," a public lecture on "big data" offered by Professor Lawrence O. Hall, from the University of South Florida.
“Deep neural networks have been shown to be very powerful for image recognition. They have provided significant increases in accuracy when applied to color images for object recognition using the ImageNet corpus. They have worked effectively when trained on big data, a million or more camera images and as many as 1000 classes of objects. This talk examines using pre-trained deep neural networks in medical imaging. How to leverage pre-trained large convolutional neural networks to extract features to enable predictions of 'disease' prognosis for two types of cancer will be shown. Results for CT images of lung nodules/tumors and MR images of brain cancer will be discussed. Transfer learning through the extraction of deep features will be shown to be a promising feature selection strategy, enabling the most accurate prognosis predictions on the data sets to be discussed.”
– Professor Lawrence O. Hall
The Notre Dame Institute for Advanced Study is also pleased to announce informal talks by Professor Hall with graduate and undergraduate students during the afternoons of Thursday, November 10 and Friday, November 11 respectively. Interested students should contact NDIAS Associate Director Don Stelluto (firstname.lastname@example.org).
Lawrence O. Hall, a Distinguished University Professor and the Chair of the Department of Computer Science and Engineering at the University of South Florida, presents on his ongoing research. His research interests lie in distributed machine learning, extreme data mining, bioinformatics, pattern recognition and integrating AI into image processing. The exploitation of imprecision with the use of fuzzy logic in pattern recognition, AI and learning is a research theme.
Hall has authored or co-authored over 80 publications in journals as well as many conference papers and book chapters. Recent publications have appeared in IEEE Access, Pattern Recognition, IEEE Transactions on Fuzzy Systems, and the Journal of Magnetic Resonance Imaging. According to Google Scholar his research work has been cited over 12,000 times. He has received over 3M in research funding from agencies such as the National Science Foundation, National Institutes of Health, Department of Energy, NASA, etc.
He is a fellow of the IEEE, the AAAS, and IAPR. He received the Norbert Wiener award in 2012 from the IEEE SMC Society. In 2015 he was a Distinguished Visiting Professor at the University of Technology, Sydney. He received the IEEE SMC Society Outstanding contribution award in 2008. He received an Outstanding Research achievement award from the University of South Florida in 2004. He is a past president of NAFIPS,the former vice president for membership of the SMC society, and he was the President of the IEEE Systems, Man and Cybernetics society for 2006-7.
He was the Editor-In-Chief of the IEEE Transactions on Systems, Man and Cybernetics, Part B, 2002-05. He served as the first Vice President for Publications of the IEEE Biometrics Council. He is currently on the IEEE Publications and Services Products Board and Chairs its Strategic Planning Committee. He also Chairs the IEEE PCC and serves as associate editor for IEEE Transactions on Fuzzy Systems, International Journal of Intelligent Data Analysis, the International Journal of Pattern Recognition and Artificial Intelligence and International Journal of Approximate Reasoning. He is on the IEEE Access editorial board.