no code implementations • 30 Jul 2020 • Rui Li, Jianbo Yang, Xianguo Tuo, Rui Shi
In this work, we investigated the performance of eight fitness functions attached to the genetic algorithm (GA) and the differential evolution algorithm (DEA) used for unfolding four neutron spectra selected from the IAEA 403 report.
no code implementations • 2 Mar 2018 • Kai-Lang Yao, Wu-Jun Li, Jianbo Yang, Xinyan Lu
Recently, geometric deep learning on graphs (GDLG) is proposed to solve the GMC problem, showing better performance than existing GMC methods including traditional graph regularization based methods.
2 code implementations • 31 Mar 2017 • Zhiguang Wang, Jianbo Yang
We proposed a deep learning method for interpretable diabetic retinopathy (DR) detection.
no code implementations • 1 Dec 2014 • Francesco Renna, Liming Wang, Xin Yuan, Jianbo Yang, Galen Reeves, Robert Calderbank, Lawrence Carin, Miguel R. D. Rodrigues
These conditions, which are reminiscent of the well-known Slepian-Wolf and Wyner-Ziv conditions, are a function of the number of linear features extracted from the signal of interest, the number of linear features extracted from the side information signal, and the geometry of these signals and their interplay.
no code implementations • NeurIPS 2014 • Jianbo Yang, Xuejun Liao, Minhua Chen, Lawrence Carin
This paper is concerned with compressive sensing of signals drawn from a Gaussian mixture model (GMM) with sparse precision matrices.
no code implementations • CVPR 2014 • Xin Yuan, Patrick Llull, Xuejun Liao, Jianbo Yang, Guillermo Sapiro, David J. Brady, Lawrence Carin
A simple and inexpensive (low-power and low-bandwidth) modification is made to a conventional off-the-shelf color video camera, from which we recover {multiple} color frames for each of the original measured frames, and each of the recovered frames can be focused at a different depth.
no code implementations • 14 Feb 2013 • Xin Yuan, Jianbo Yang, Patrick Llull, Xuejun Liao, Guillermo Sapiro, David J. Brady, Lawrence Carin
This paper introduces the concept of adaptive temporal compressive sensing (CS) for video.