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Foreground segmentation is a fundamental method in computer vision. Traditional foreground segmentation algorithms are sensitive to blurry degree of background, smooth foreground regions and camouflage foreground. To deal with these problems, we use light field images as input by exploiting its focusness cue. In this paper, we propose an automatic foreground segmentation algorithm for light field...
This paper presents robust controller design for damping of inter-area mode oscillations in two area test system by Thyristor Controlled Series Capacitor (TCSC) using global signal. The stabilizing signal is obtained from phasor measurement units (PMUs) located in both areas of test power system. Residue analysis is carried out to decide the best control signals for damping of critical mode. H∞ loop...
This paper studies the problem of planning collision-free dynamically feasible trajectories for a team of autonomous unmanned aerial vehicles (UAVs) in real-time, where the UAVs try to fly through a complex 3-D environment to reach their specified destinations. First, the cooperative trajectory planning problem is mathematically formulated as a decentralized receding horizon optimal control problem...
Periodic inspections are necessary to keep railroad tracks in state of good repair and prevent train accidents. Automatic track inspection using machine vision technology has become a very effective inspection tool. Because of its non-contact nature, this technology can be deployed on virtually any railway vehicle to continuously survey the tracks and send exception reports to track maintenance personnel...
This paper presents a combinatorial rigidity approach to measure rigidity and redundant rigidity for wireless sensor and robot networks. Redundant rigidity is a necessary condition for global rigidity, which is desirable for network localization. Redundant rigidity also provides rigidity robustness in formation control and network localization against structural changes, such as link losses. In 2-space,...
Individual face detection and identification technologies have improved greatly in terms of accuracy, but there exist challenges of adoption in Consumer Electronic devices due to the lack of large training databases pertaining to the individual. With 1 or 2 images to train about the current user, it is nearly impossible to identify a person's face robustly. So, in this paper we propose the use of...
Nowadays there is an increasing interest on deploying spoken conversational agents to provide ubiquitous Question and Answering information to customers about corporate services and commercial products and supporting different users' devices such as PC desktops or mobile phones. Unfortunately, creating an accurate system requires a lot of handwork, where developers must consider several factors such...
A notion of fc-robustness for complex networks has received much attention recently. The motivation for this notion of robustness is to measure the effectiveness of local-information-based diffusion algorithms in the presence of adversarial nodes. In this paper, we first correct the relationship between fc-robustness and fc-connectivity studied in related work. Then we derive a sharp zero-one law...
The highway electromechanical system is an important support to ensure normal operation of the highway. Currently, the cyclical and integral maintenance strategy was mainly adopted. In order to improve the equipment utilization and economic performance, a key equipment search algorithm based on complex network structure is presented in this paper, which gives a new way with differentiation for highway...
This paper addresses an optimal path problem in which the travel time within the travel network is subject to uncertainty. Many relevant works in the literature model the uncertainty using a random variable, however in many cases the underlying distribution of the uncertainty is not accurately determined and a solution obtained under a presumed distribution can perform poorly in practice. In this...
Due to their lower complexity that make them affordable for practical applications, suboptimal MIMO-OFDMA downlink resource allocation (RA) algorithms have attracted significant attention. In this paper, a novel suboptimal RA algorithm is introduced and shown to achieve higher efficiency performance in comparison with other existing techniques. RA algorithms that are robust against CSIT imperfections,...
This paper proposes a novel multi-scale image hashing method by using the location-context information of the features generated by adaptive local feature extraction techniques. The adaptive local feature extraction method is proposed for more robust feature descriptors. The global hash is calculated to determine whether the received image has been maliciously tampered. The multi-scale hash is calculated...
Many different image stitching algorithms, and mechanisms to assess their quality have been proposed by different research groups in the past decade. However, a comparison across different stitching algorithms and evaluation mechanisms has not been performed before. Our objective is to recognize the best algorithm for panoramic image stitching. We measure the robustness of different algorithms by...
As one of the recent popular discriminative training methods, Minimum Classification Error (MCE) training aims at efficiently developing high-performance classifiers through the minimization of smooth (differentiable in classifier parameters) classification error count loss. However, MCE training, sometimes referred to as Functional Margin (FM) MCE training, does not necessarily guarantee training...
Through many researches on CBIR (Content Based Image Retrieval), local image features defined on keypoints are proved to be effective for occlusion-robust image retrieval. However, not all features in an image contribute correct image retrieval, i.e. some are unstable and some commonly appear in other images. For representing the importance of the image features, Diverse Density (DD) based index-feature...
In this article we present Miuz, a robustness index for complex networks. Miuz measures the impact of disconnecting a node from the network while comparing the sizes of the remaining connected components. Strictly speaking, Miuz for a node is defined as the inverse of the size of the largest connected component divided by the sum of the sizes of the remaining ones. We tested our index in attack strategies...
Dynamically substructured system (DSS) technique is increasing recognized in the testing field. A DSS method decomposes an entire system into several substructures, which are tested numerically or physically, but run as a whole like the original system. Thus, the advantages of DSS include flexibility, space-saving, and cost-reduction. In a DSS test, actuators produce unexpected disturbance, when transferring...
The Steered Response Power using the Phase Transform weight (SRP-PHAT) has been shown to be robust in noisy and reverberant conditions. Also, volume contraction has been applied effectively to trap the global maximum for densely-hilly 3-D spaces like the SRP. However, previous methods have suffered from the presence of peaks representing multiple talkers in close proximity as is likely in a conversational...
Class discovery, which aims to identify the underlying category structure, is an important issue in pattern recognition and knowledge discovery. The key task in class discovery is to estimate the number of classes. Classical estimation approaches usually face the problems of low accuracy, high complexity, or difficulty in choosing an appropriate penalty function. In this paper, an effective class...
Two "heterogeneous" information dissemination networks were established on the basis of sets of actual "rum or information" and "anti-rum or information" dissemination data involving a real micro logging event. Through empirical analysis of degree centrality, between ness centrality and closeness centrality, it was discovered that all three centrality indexes of the two...
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