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Linear matching (LM) is a simple and effective method for solving image matching problems. In many cases, image matching problems are nonlinear due to involvement of the geometric transformations; therefore, an essential step for utilizing linear models for image matching is to linearize the geometric transformation matrices that introduce nonlinear terms into image matching problems. Existing LM...
This paper develops a set-membership estimation algorithm for identification of time-varying parameters in linear models, where both additive and multiplicative uncertainties are considered explicitly. We show that a recursive algorithm we develop is capable of providing tight overbounds on the feasible solution set. Examples are considered to demonstrate the utility and effectiveness of the algorithm,...
In Real-Time Bidding (RTB) advertising, evaluating the Click-Through Rate (CTR) of a bid request and an ad is important for bidding strategy optimization on Demand-Side Platforms (DSPs). The regression-based approaches are popular for CTR estimation in RTB since this kind of approach is highly efficient and scalable. The information of the bid request and the ad contains categorical attributes (such...
In wireless networks, determining the error bit positions within a packet at the receiver can improve the wireless retransmission efficiency in wireless communications. In this paper, we propose an Error Position Estimating Coding (EPEC) scheme based on Error Estimating Coding (EEC). Specifically, we divide data bits into several groups and indicate the group number individually to implement error...
Kriging-based Global optimization has been proposed and extensively used for solving black-box optimization problems with expensive function evaluations. The performance of such algorithm relies heavily on the effectiveness of the infill criterion that is used to decide which point to evaluate next. Two common infill criteria are, the probability of improvement (PI) and the expected improvement (EI)...
Condition monitoring and condition-based maintenance can reduce maintenance costs and improve operation safety of vehicles across the full spectrum of transportation domain, including automotive, rail, air and marine applications. In this paper, a set-membership condition monitoring framework is proposed to detect aging and health degradation for dual fuel engines based on simultaneous input and parameter...
We propose a residual-consensus driven linear matching algorithm for simultaneous geometric parameter and point correspondence estimation. Using the linearization technique, we quantize geometric transformation into discrete levels with regard to each correspondence matrix. We identify the uncontaminated models by evaluating the statistical coherent of residual ordering and Maximum mean discrepancy...
Local image features show a high degree of repeatability, while their local appearance usually does not bring enough discriminative pattern to obtain a reliable matching. In this paper, we present a new object matching algorithm based on a novel robust estimation of residual consensus and flexible spatial consistency filter. We evaluate the similarity between different homography model via two-parameter...
Compressed sensing (CS) can give a sparse representation of compressible signals. We consider the problem of blind signal recovery based on CS and propose a novel algorithm for sparse signal reconstruction with low complexity. From the CS sampled measurements, we first get the signal parameters' estimation, such as the carrier frequency, and reconstruct the narrow band signal using the estimated result...
A fast and efficient algorithm is proposed to estimate the direction of arrival (DOA) of the signals impinging on an uniformly located linear array. Unlike the classical MUSIC method, it is not needed for the method proposed in this paper to have the number of the signal sources known as a prior knowledge. The proposed method only needs the forward recursions of multistage Wiener filter (MSWF) to...
Various 3D applications require accurate and smooth depth map, and post-processing is necessary for depth map directly generated by different correspondence algorithms. A hierarchical joint bilateral filtering method is proposed to improve the coarse depth map. By first carrying out depth confidence measuring, pixels are put into different categories according to their matching confidence. Then the...
Feature selection is a crucial step in the supervised learning process. Traditional feature selection methods based on mutual information cannot directly handle the feature set with hybrid continuous and categorical features, and cannot dynamically eliminate the redundant features in the feature selection process. Resort to mutual information, a hybrid feature selection method named PGFB is proposed...
Seamless image processing concerns stitching parts of images in a visually natural manner. In this paper, we present a seamless processing method which unifies Featuring, Optimal seam method and some recent gradient domain methods including Poisson image editing, Drag-and-drop pasting and GIST. To evaluate the processing quality visually, a variational energy function is proposed to compute both the...
This paper mainly aims at BPSK signals to establish and validate a timing estimation method named as WP.Z algorithm that uses two samples/symbol sampling rate and its modified algorithm. Both of them have been carried on modeling and simulating in detail and their performance is evaluated under various parameters. It is not only discussed the accuracy, astringency and applied bound between two algorithms,...
Existing power diode models in most time-domain circuit simulators cannot accurately present the reverse recovery characteristics of actual diode devices with fast simulation speed. Ma-Lauritzen model is a relatively simple solution for modeling the reverse recovery of diode with reasonable accuracy but so far little result has been reported on the methodology and process for applications in circuit...
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