In this paper, a new hybrid conjugate gradient algorithm is proposed for solving unconstrained optimization problems. This new method can generate sufficient descent directions unrelated to any line search. Moreover, the global convergence of the proposed method is proved under the Wolfe line search. Numerical experiments are also presented to show the efficiency of the proposed algorithm, espe...

Techniques for the separate/joint optimization of error-feedback and realization are developed to minimize the roundoff noise subject to l2-norm dynamic-range scaling constraints for a class of 2-D state-space digital filters. In the joint optimization, the problem at hand is converted into an unconstrained optimization problem by using linearalgebraic techniques. The unconstrained problem obta...

In this paper, we introduce individualness of detection candidates as a complement to objectness for pedestrian detection. The individualness assigns a single detection for each object out of raw detection candidates given by either object proposals or sliding windows. We show that conventional approaches, such as non-maximum suppression, are sub-optimal since they suppress nearby detections us...