In this paper, a fault-tolerant routing in 2-D meshes with dynamic faults is provided. It is based on an early work on minimal routing in 2-D meshes with static faults. Unlike man...
Recurrent neural networks serve as black-box models for nonlinear dynamical systems identification and time series prediction. Training of recurrent networks typically minimizes t...
In this paper, we design and implement an efficient technique for parallel evidence propagation on state-of-the-art multicore processor systems. Evidence propagation is a major ste...
In the k-nearest neighbor (KNN) classifier, nearest neighbors involve only labeled data. That makes it inappropriate for the data set that includes very few labeled data. In this ...
Abstract. Gradient-domain compositing is an essential tool in computer vision and its applications, e.g., seamless cloning, panorama stitching, shadow removal, scene completion and...