Design of a Compact Reversible Carry Look-Ahead Adder Using Dynamic Programming Abstract: This paper presents a new method for designing a reversible carry look-ahead adder (RCLA) based on dynamic programming. In this method, we propose a faster technique for generating carry output, which also outperforms the existing ones in terms of number of operations. In […]
Robust Visual Tracking via Convolutional Networks without Training Abstract Deep networks have been successfully applied to visual tracking by learning a generic representation offline from numerous training images. However, the offline training is time-consuming and the learned generic representation may be less discriminative for tracking specific objects. In this paper, we present that, even without offline training with a large amount of auxiliary data, simple two-layerconvolutional networks can be powerful enough to […]