T1.5

JOINT DEEP IMAGE RESTORATION AND UNSUPERVISED QUALITY ASSESSMENT

Hakan Emre Gedik, Abhinau Kumar Venkataramanan, Alan Conrad Bovik, The University of Texas at Austin, United States
Session:
T1: Image/Video Analysis and Modeling II Lecture
Track:
Image and video quality assessment
Location:
Lecture Room
Presentation Time:
Tue, 19 Mar, 10:00 - 10:15 MST (UTC -7)
Presentation
Discussion
Resources
No resources available.
Session T1
T1.1 A VISUAL QUALITY ASSESSMENT METHOD FOR RASTER IMAGES IN SCANNED DOCUMENT
Justin Yang, Purdue University, United States; Peter Bauer, Todd Harris, HP Inc., United States; Changhyung Lee, Hyeon Seok Seo, HP Printing Korea Co Ltd, Korea (South); Jan P. Allebach, Fengqing Zhu, Purdue University, United States
T1.2 FROM TOPOLOGICAL SIGNATURES TO TEXTURAL PATTERNS: ENHANCING THE PRECISION OF SAND CLASSIFICATION
Ankur Yadav, Ovidiu Daescu, Zachary Sickmann, The University of Texas at Dallas, United States
T1.3 IMPROVING AGE PREDICTION: UTILIZING LSTM-BASED DYNAMIC FORECASTING FOR DATA AUGMENTATION IN MULTIVARIATE TIME SERIES ANALYSIS
Yutong Gao, Charles Ellis, Vince Calhoun, Robyn Miller, Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS): Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, Georgia, United States
T1.4 LOOK OUT FOR DANGEROUS SPIDERS: ARANEAE CLASSIFICATION USING DEEP LEARNING METHODS
Zi Deng, Jeffrey Rodriguez, University of Arizona, United States
T1.5 JOINT DEEP IMAGE RESTORATION AND UNSUPERVISED QUALITY ASSESSMENT
Hakan Emre Gedik, Abhinau Kumar Venkataramanan, Alan Conrad Bovik, The University of Texas at Austin, United States
Resources
No resources available.