[2018/06] J. Min, K. H. Jin, M. Unser, and J. C. Ye, "Grid-free localization algorithm using low rank Hankel matrix for super-resolution microscopy," is now accepted in IEEE Trans. on Image Processing [2018/06] H. Gupta, K. H. Jin, H. Q. Nguyen, M. T. McCann, and M. Unser, "CNN-Based projected gradient descent for consistent CT image reconstruction," is now published in IEEE Trans. on Medical Imaging [2018/06] K. Lee, Y. Li, K.H. Jin, and J. C. Ye, "Unified theory for recovery of sparse signals in a general transform domain," is now accepted in IEEE Trans. on Information Theory [2018/06] Code (python+tensorflow) is open [github] [2018/02] 3D ConvNet classifier for Alzheimer is now published. H. Choi and K. H. Jin, "Predicting cognitive decline with deep learning of brain metabolism and amyloid imaging," Behavioural Brain Research, vol 344, (2018), pp 103-109 This work was also featured by MIT technology review (Apr. 28.2017) link[2017/11] A Review article for inverse problem with CNN is now appeared. M. T. McCann, K. H. Jin, and M. Unser. "Convolutional Neural Networks for Inverse Problems in Imaging: A Review." IEEE Signal Processing Magazine 34.6 (2017): 85-95.[2017/11] K. H. Jin, and J. C. Ye. "Sparse and Low Rank Decomposition of a Hankel Structured Matrix for Impulse Noise Removal," IEEE Trans. on Image Processing. vol. 27, no. 3, pp. 1448-1461, March 2018.Code (matlab) is open [github] [2017/06] K. H. Jin, M.T. McCann, E. Froustey, M. Unser , "Deep Convolutional Neural Network for Inverse Problems in Imaging," IEEE Transactions on Image Processing, 26.9 (2017): 4509-4522. [The most frequently accessed document in IEEE TIP 2017.10~12, 2018.01]Code (matlab, tensorflow) is open [github] [2017] K. H. Jin, D. Lee, and J. C. Ye, "A general framework for compressed sensing and parallel MRI using annihilating filter based low-rank Hankel matrix," IEEE Transactions on Computational Imaging, vol. 2, no. 4, pp. 480-495, Dec. 2016.E-mail : kyonghwan.jin@gmail.com, kyong.jin@epfl.ch |

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