Over the years, indoor scene parsing has attracted a growing interest in the computer vision community. Existing methods have typically focused on diverse subtasks of this challenging problem. In particular, while some of them aim at segmenting the image i ...
Approximation circuits offer superior performance (speed and area) compared to traditional circuits at the cost of computational accuracy. The accuracy of the results in approximation circuits is evaluated based on several error metrics such as worst-case ...
Stochastic models for interacting processes feature a dimensionality that grows exponentially with the number of processes. This state space explosion severely impairs the use of standard methods for the numerical analysis of such Markov chains. In this wo ...
State-of-the-art wearable devices such as embedded biomedical monitoring systems apply voltage scaling to lower as much as possible their energy consumption and achieve longer battery lifetimes. While embedded memories often rely on Error Correction Codes ...
We propose to model the acoustic space of deep neural network (DNN) class-conditional posterior probabilities as a union of low- dimensional subspaces. To that end, the training posteriors are used for dictionary learning and sparse coding. Sparse represen ...
