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In this paper, we propose an image registration algorithm based on improved SIFT (Scale-Invariant Feature Transform) algorithm and essential matrix estimation based on RANSAC (Random Sample Consensus) and AC-RANSAC (A Contrario RANSAC) algorithm. So that in the 3D reconstruction, we can directly restore the parameters of the camera by using the essential matrix model estimated by image registration...
With the increasing number of public available training data for face alignment, the regression-based methods attracted much attention and have become the dominant methods to solve this problem. There are two main factors, the variance of the regression target and the capacity of the regression model, affecting the performance of the regression task. In this paper, we present a Stacked Hourglass Network...
In this paper, we study the optimum sensing of a time-varying random event with a sensor powered by energy harvesting devices. The system aims at reconstructing a band-unlimited continuous-time random process by using discrete-time samples collected by a sensor. Due to the random nature of the harvested energy, the sensor might not have sufficient energy to perform a sensing operation at a desired...
Level set estimation (LSE) is the process of classifying the region(s) that the values of an unknown function exceed a certain threshold. It has a wide range of applications such as spectrum sensing or environment monitoring. In this paper, we study the the optimal LSE of a linear random field that changes with respect to time. A linear sensor network is used to take discrete samples of the spatially-temporally...
Functional Engineering Change Order (ECO) is necessary for logic rectification at late design stages. Existing works mainly focus on identifying a minimal logic difference between the original netlist and the revised netlist, which is called a patch. The patch is then implemented by technology mapping using spare cells. However, there may be insufficient spare cells around the physical location of...
This paper presents a model for location anonymous area estimation, which establishes the related Bayesian inference network by making full use of the time-varying characteristic of person traffic or vehicle traffic, thus implementing the dynamical estimation method of minimum anonymous area. Integrating the real data, the method makes the prediction, therefore it is more accurate. The model in this...
In this paper, we study the optimum estimation of a continuous-time random process by using discrete-time samples taken by a sensor powered by energy harvesting power sources. The system employs a best-effort sensing scheme to cope with the stochastic nature of the energy harvesting sources. The best-effort sensing scheme defines a set of equally-spaced candidate sensing instants, and the sensor performs...
In this paper, we study the optimal sampling policy for an energy harvesting sensing system, which is designed to estimate a wide-sense stationary random process by using discrete-time samples collected by a sensor. The energy in the sensor is consumed by taking observations and is replenished randomly with energy harvested from the ambient environment. Our goal is to identify the optimal sampling...
Level set estimation (LSE) is the process of using noisy observations of an unknown function to estimate the region(s) where the function values lie above a given threshold. It has a wide range of applications in many scientific and engineering areas, such as spectrum sensing or environment monitoring. In this paper, we study the optimum LSE of a time-varying random field under a total power constraint...
this article will use the generalized ridge regression in system harmonic impedance analysis and the harmonic evaluation. Based on the equivalent circuit of the system, users can obtain system harmonic impedance, the background harmonic and common connection point, the analytical expression of the harmonic. Using the harmonic voltage and current data which will be got in the common connection point,...
Accurate peak power measurement requires detailed switching and delay information for each signal over the entire simulation. Performing a full signal dump and power calculation for a long simulation run usually spends a large amount of time and disk space. In this paper, we propose an Essential-signal-based methodology which only performs power analysis over a small subset of the original simulation...
In this paper, we utilize rough set theory as a tool to deal with the problem of null-value estimation in an incomplete information system, a rating mechanism in collaborative filtering technology is introduced into this paper for the weakness of null value estimation based on similar relational algorithm (SIM-EM), such as no sparse degree process and low accuracy, and an improved null value estimation...
In this paper, we address a driver behavior reconstruction problem which is important to enhance traffic safety. More specifically, the task in this study is to estimate the longitude tire force which can be transferred to the corresponding throttle/brake positions under the assumption that the steering angles are known. Although the sensors mounted on the throttle/brake pedals can directly measure...
This paper proposes an automated steering control system for passenger cars. The control strategy used is a look-down reference system which uses a sensor at the front bumper to measure the lateral displacement and a GPS to measure the heading orientation. Firstly, the road curvature estimator is designed based on the steering angle. Secondly, the steering angles can be estimated by using the sensor...
Grid impedance estimation is important in monitoring and protection of wide-area power systems. In this paper, a recursive least squares estimation algorithm with a forgetting factor is proposed to identify impedance matrix of electrical power grids. This new approach is based on synchronized phasor measurements and makes it possible to track changing parameters due to grid reconfiguration and load...
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