SSP-O.2: Sparse Signal Processing and Deep Learning II |
Symposium: Symposium on Sparse Signal Processing and Deep Learning |
Session Type: Oral |
Time: Tuesday, November 14, 14:00 - 15:30 |
Location: Mont-Royal |
Session Chair: Chinmay Hegde, Iowa State University |
14:00 - 14:18 |
SSP-O.2.1: FAST ADMM SOLVER FOR REWEIGHTED TOTAL VARIATION IMAGE DECONVOLUTION AND INPAINTING |
John Lee; Georgia Institute of Technology |
Christopher Rozell; Georgia Institute of Technology |
14:18 - 14:36 |
SSP-O.2.2: HOW TO DEAL WITH MULTI-SOURCE DATA FOR TREE DETECTION BASED ON DEEP LEARNING |
Lionel Pibre; LIRMM laboratory, University of Montpellier / Berger-Levrault Company |
Marc Chaumont; LIRMM laboratory, University of Montpellier / University of Nîmes |
Gérard Subsol; LIRMM laboratory, University of Montpellier / CNRS |
Dino Ienco; IRSTEA |
Mustapha Derras; Berger-Levrault Company |
14:36 - 14:54 |
SSP-O.2.3: HYPERSPECTRAL IMAGE FUSION BASED ON NON-FACTORIZATION SPARSE REPRESENTATION AND ERROR MATRIX ESTIMATION |
Xiaolin Han; Tsinghua University |
Jiqiang Luo; Beijing Institute of Technology |
Jing Yu; Beijing University of Technology |
Weidong Sun; Tsinghua University |
14:54 - 15:12 |
SSP-O.2.4: JOINT-SPARSE DICTIONARY LEARNING: DENOISING MULTIPLE MEASUREMENT VECTORS |
Prerna Singh; IIITD |
Ramy Hussein; University of British Columbia |
Angshul Majumdar; IIITD |
Rabab Ward; University of British Columbia |
15:12 - 15:30 |
SSP-O.2.5: DEMIXING STRUCTURED SUPERPOSITION SIGNALS FROM PERIODIC AND APERIODIC NONLINEAR OBSERVATIONS |
Mohammadreza Soltani; Iowa State University |
Chinmay Hegde; Iowa State University |