Fall 2017 – Spring 2018 Archive
This seminar is organized by Drs. Cao and Lou. If you have questions about this seminar please contact Dr. Yan Cao. The journal club meets on Tuesdays at 10:00-11:00am in FO 2.610F in Spring 2018. The members include both graduate and undergraduate students. Each week one of the students presents a paper in the field of image and signal analysis of his/her interest. The chosen paper will be announced prior to the meeting. The goal of the journal club is to introduce graduate and undergraduate students to image and signal analysis research and create an open venue for friendly but lively scientific discussion.
| Date | Speaker | Title | Paper |
| April 17 | Russell Hart | Colorful Image Colorization | Colorful Image Colorization, R. Zhang, P. Isola and A.A. Efros, arXiv:1603.08511v5, 2016. |
| April 10 | Rajendra Khatri | A Fast Learning Algorithm for Deep Belief Nets | A Fast Learning Algorithm for Deep Belief Nets, G.E. Hinton, S. Osindero and Y. Teh, Neural Computation 18, pp. 1527–1554, 2006. |
| April 3 | Mohammadmedhi Akhavan |
Richardson-Lucy method iterative deconvolution and their applications | Richardson–Lucy Algorithm With Total Variation Regularization for 3D Confocal Microscope Deconvolution, N. Dey, L. Blanc-Feraud, C. Zimmer, P. Roux, Z. Kam, J. Olivo-Marin and J. Zerubia, Microscopy Research and Technique, 69, pp. 260-266, 2006. |
| March 27 | Jun Zhang | Fast linearized ALMs for image denoising problems based on fourth-order PDEs | A Fast Augmented Lagrangian Method for Euler’s Elastica Models, Y. Duan, Y. Wang and J. Hahn, Numer. Math. Theor. Meth. Appl., 6(1), pp 47-71, 2013.
A Fast Algorithm for a Mean Curvature Based Image Denoising Model Using Augmented Lagrangian Method, W. Zhu, X. Tai and T. Chan, Global Optimization Methods, LNCS 8293, pp. 104–118, 2014. |
| March 20 | Mujibur Chowdhury | Total bounded variation-based Poissonian images recovery by split Bregman iteration |
Total bounded variation-based Poissonian images recovery by split Bregman iteration, X. Liu and L. Huang, Mathematical Methods in the Applied Sciences, 35, pp 520-529, 2012. |
| March 6 | Varun Balaraju | Long Short-Therm Memory Networks | Long Short-Therm Memory, S. Hochreiter and J. Schmidhuber, Neural Computation, 9(8), pp. 1735-1780, 1997. |
| Feb. 27 | Yaghoub Rahimi | Necessary and Sufficient Conditions for Sparse Recovery | Unified sufficient conditions for uniform recovery of sparse signals via nonconvex minimizations, H. Tran and C. Webster, arXiv:1710.07348. |
| Feb. 20 | Siyuan Wang | Clustering Algorithms |
Topics: k-means, fuzzy c-means and mixture models. |
| Feb. 13 | Sijie Shen | Frequency decomposition of conditional Granger causality and application to multivariate neural field potential data | Frequency decomposition of conditional Granger causality and application to multivariate neural field potential data, Y. Chena, S. L. Bressler, M. Ding, Journal of Neuroscience Methods, vol. 150, pp 228–237, 2006. |
| Feb. 6 | Tian Jiang | Deep Residual Learning for Image Recognition | Deep Residual Learning for Image Recognition, K. He, X. Zhang, S. Ren, J. Sun, In CVPR 2016. |
| Jan. 23 | Organization Meeting | ||
| Dec. 5 | Rajendra Khatri | Diffeomorphic Nonlinear Transformations: A local Parametric Approach for Image Registration | Diffeomorphic Nonlinear Transformations: A local Parametric Approach for Image Registration, R. Narayanan, J.A. Fessler, H. Park, and C.R. Meyer, Information Processing in Medical Imaging, LNCS, volume 3565, pp 174-185, 2005. |
| Nov. 27 | Md Mujibur Chowdhury | Total Generalized Variation | Total Generalized Variation, K. Bredies, K. Kunisch, and T. Pock, SIAM J. Imaging Sciences, Vol. 3, No. 3, pp. 492–526, 2010. |
| Nov. 7 | Mohammadmedhi Akhavan |
One Dimensional Bar-code Deblurring | |
| Oct. 31 | Siyuan Wang | Linear Filtering | |
| Oct. 24 | Russell Hart | Deblurring Text Images Using a Convolutional Neural Network in Tensorflow |
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| Oct. 17 | Mengqi Hu | Compressive Sensing Imaging for General Synthetic Aperture Radar Echo Model Based on Maxwell’s Equations | Compressive sensing for a general SAR imaging model based on Maxwell’s equations, B. Sun, H. Gu, M. Hu, Z. Qiao, Proc. of SPIE Vol. 9484, 2015.
Compressive sensing imaging for general synthetic aperture radar echo model based on Maxwell’s equations, B. Sun, Y. Cao, J. Chen, C. Li, Z. Qiao, EURASIP Journal on Advances in Signal Processing 2014, 2014:153. |
| Oct. 10 | Brendan Caseria and Alsadig Ali | Automatic Extraction of Cell Nuclei from Pathological Images | Automatic extraction of cell nuclei from H&E-stained histopathological images, F. Yi, J. Huang, Y. Xie, G. Xiao, Journal of Medical Imaging, 4(2), 2017. |
| Oct. 3 | Noor Abbas | Morphological Image Processing | Practical Image and Video Processing Using MATLAB, Chapter 13, O. Marques, Hoboken, N.J. : J. Wiley & Sons/IEEE Press, 2011. |
| Sept. 26 | Tian Jiang | Deep Learning | Deep learning, Y. LeCun, Y. Bengio, G. Hinton, Nature, Vol 521, 436-444, 2015. |
| Sept. 19 | Sijie Shen | Causality Detection | Detecting Causality in Complex Ecosystems, G. Sugihara, R. May, H. Ye, C. Hsieh, E. Deyle, M. Fogarty, S. Munch, Science, vol 338, 496-500, 2012. |
| Sept. 12 | Yaghoub Rahimi | Logistic Regression | |
| Sept. 5 | Organization meeting |