Compressive Sensing (CS) combines sampling and compression into a single subNyquist linear measurement process for sparse and compressible signals. In this paper, we extend the th...
Volkan Cevher, Marco F. Duarte, Chinmay Hegde, Ric...
Monte Carlo methods and their subsequent simulated annealing are able to minimize general energy functions. However, the slow convergence of simulated annealing compared with more ...
This is the sample implementation of a Markov random field based image segmentation algorithm described in the following papers:
1. Mark Berthod, Zoltan Kato, Shan Yu, and Josi...
Object models based on bag-of-words representations can achieve state-of-the-art performance for image classification and object localization tasks. However, as they consider obje...
As CMOS devices and operating voltages are scaled down, noise and defective devices will impact the reliability of digital circuits. Probabilistic computing compatible with CMOS o...
Kundan Nepal, R. Iris Bahar, Joseph L. Mundy, Will...