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检索条件"主题词=fusion algorithm"

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Comparison study on self-calibration level fusion algorithm with Bayes estimation theory for wood drying kiln industry process

Comparison study on self-calibration level fusion algorithm ...

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IEEE International Conference on Mechatronics and Automation

作者： Cao, Jun Zhang, Jiawei Liu, Yixing Northeast Forestry Univ Sch Electromec Engn Harbin 150040 Heilongjiang Peoples R China Northeast Forestry Univ Key Lab Bio Based Mat Sci & Technol Harbin 150040 Heilongjiang Peoples R China

ISBN: (纸本)9781424408276

Since the complex operation environment in wood drying kiln, the precision of lumber moisture content (LMC) is affected greatly with the ambient parameters which have closed multi-couple and correlated relation with them. Based on above reasons background, a comparison study on self-calibration level fusion algorithm based Bayes estimation theory for wood drying-kiln industry process is presented in this paper. Staring with analyzing the existing problems of LMC measured by individual sensor, we then put forward the architecture of multi-sensor data fusion for LMC measuring system. The performance of self-calibration level is detailed discussed. The technique of the determination of confidence distance and optimal fusion set, the total probability maximum algorithm, the Bayes estimation algorithm, and arithmetic averaging method are investigated respectively. Comparison the simulation results, a self-calibration fusion algorithm based Bayes estimation theory is determined.

关键词： fusion algorithm Bayes estimation theory self-calibration level wood drying kiln

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Preprocessing of Kinect Depth Map Sequence Compression Based on fusion algorithm 3

Preprocessing of Kinect Depth Map Sequence Compression Based...

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3rd IEEE International Conference on Image, Vision and Computing (ICIVC)

作者： Ha, Rui Liu, Pengyu Jia, Kebin Beijing Univ Technol Fac Informat Technol Beijing 100124 Peoples R China Beijing Lab Adv Informat Networks Beijing 100124 Peoples R China Beijing Univ Technol Beijing Adv Innovat Ctr Future Internet Technol Beijing 100124 Peoples R China Beijing Univ Technol Beijing Key Lab Computat Intelligence & Intellige Beijing 100124 Peoples R China

ISBN: (纸本)9781538649916

The depth map sequence collected by Kinect can be transmitted through the existing video compression coding platform, which saves a lot of computing resources and saves a lot of computing resources than the conversion of the point cloud data. However, the depth map sequence collected by the Kinect has an unstable characteristic in the time domain, so the prediction of the residual error is not accurate after entering the video encoder, which will consume unnecessary coding resources. In this paper, through the supplementary analysis of the work in the literature [10], an approximate three-dimensional volume algorithm is introduced to generate a stable reference frame for the Kinect depth map sequence. In addition, this article also distinguishes between dynamic macroblocks and static macroblocks in the depth map to determine whether to skip the search steps in the HEVC (efficient video coding) interframe prediction;finally, compared with the unprocessed Kinect depth map sequence in the bit mice. The performance of E, run time, PSNR (peak signal-to-noise ratio) and 3D reconstruction are better than those of the latter.

关键词： depth map fusion algorithm HEVC 3D reconstruction

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A SIMPLE fusion algorithm OF POLAR-ORBITING AND GEOSTATIONARY SATELLITE DATA FOR THE ESTIMATION OF SURFACE SHORTWAVE FLUXES 36

A SIMPLE FUSION ALGORITHM OF POLAR-ORBITING AND GEOSTATIONAR...

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36th IEEE International Geoscience and Remote Sensing Symposium (IGARSS)

作者： Chen, Ling Yan, Guangjian Ren, Huazhong Wang, Tianxing Beijing Forestry Univ Sch Forestry Minist Educ Key Lab Silviculture & Conservat Beijing 100083 Peoples R China Beijing Normal Univ Sch Geog State Key Lab Remote Sensing Sci Beijing 100875 Peoples R China Peking Univ Inst Remote Sensing & Geog Informat Syst Beijing 100871 Peoples R China Chinese Acad Sci Inst Remote Sensing Applicat Beijing 100101 Peoples R China

ISBN: (纸本)9781509033324

Based on our previous studies, a simple fusion algorithm is proposed to estimate surface shortwave fluxes with polar-orbiting and geostationary satellite data. A shortwave flux component of one geostationary moment can be retrieved by only five inputs which include the known flux of one polar-orbiting moment, solar zenith angles and cloud fractions of the two moments. The preliminary validations are performed in terms of both the simulated and realistic datasets. The R-2 for each component is higher than 0.90 in the simulated case. The accuracy is relatively lower for the more complicated realistic situations. All of the validation results show that the simple and practical fusion algorithm has the potential to estimate surface shortwave fluxes with acceptable accuracy. With the combination of polar-orbiting (MODIS) and geostationary (Fengyun-2C) satellite data, surface shortwave fluxes with the temporal resolution of one hour were retrieved over the Tibetan Plateau.

关键词： polar-orbiting geostationary fusion algorithm MODIS Fengyun-2C

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A 2.5D YOLO-BASED fusion algorithm FOR 3D LOCALIZATION OF CELLS 53

A 2.5D YOLO-BASED FUSION ALGORITHM FOR 3D LOCALIZATION OF CE...

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53rd Asilomar Conference on Signals, Systems, and Computers (ACSSC)

作者： Ziabari, Amirkoushyar Rose, Derek C. Eicholtz, Matthew R. Solecki, David J. Shirinifard, Abbas Oak Ridge Natl Lab Oak Ridge TN 37830 USA Florida Southern Coll Lakeland FL USA St Jude Childrens Res Hosp 332 N Lauderdale St Memphis TN 38105 USA

ISBN: (纸本)9781728143002

Advances in microscopy techniques such as lattice-light-sheet, confocal, two-photon, and electron microscopy have enabled the visualization of 3D image volumes of tightly packed cells, extracellular structures in tissues, organelles, and subcellular components inside cells. These images sampled by 2D projections are often not accurately interpreted even by human experts. As a use case we focus on 3D image volumes of tightly packed nuclei in brain tissue. Due to out-of-plane excitation and low resolution in the z-axis, non-overlapping cells appear as overlapping 3D volumes and make detecting individual cells challenging. On the other hand, running 3D detection algorithms is computationally expensive and infeasible for large datasets. In addition, most existing 3D algorithms are designed to extract 3D objects by identifying the depth in the 2D images. In this work, we propose a YOLO-based 2.5D fusion algorithm for 3D localization of individual cells in densely packed volumes of nuclei. The proposed method fuses 2D detection of nuclei in sagittal, coronal, and axial planes and predicts six coordinates of the 3D bounding cubes around the detected 3D cells. Promising results were obtained on multiple examples of synthetic dense volumes of nuclei imitating confocal microscopy experimental datasets.

关键词： Deep Learning (DL) YOLO fusion algorithm Localization Cells

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Multi-mode fusion algorithm for robust dim point-like target detection

Multi-mode fusion algorithm for robust dim point-like target...

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Conference on Acquisition, Tracking, and Pointing XVII

作者： Lim, ET Shue, L Ronda, V Inst Infocomm Res Singapore 119613 Singapore

ISBN: (纸本)0819449415

This paper presents a multi-mode fusion algorithm for detection and tracking of dim, point-like target. The key contribution of this paper includes the effective fusion approach to harvest the advantages and complement the disadvantages of various algorithms using conditional voting. From qualitative analysis, these algorithms are separated into two classes, i.e. main and supporting algorithms. In the multi-mode fusion algorithm high confidence is placed on the main algorithms with supporting algorithms used to further reduce the false alarm. The main algorithms trigger a voting process and detection is confirmed true if any of the supporting algorithms report detection. The multi-modal fusion algorithm has lower false alarm and moderate true detection rate compared to any individual algorithm namely, Triple Temporal Filter, Frame Differencing, Continuous Wavelet Transform, Max-median and 2-D Mexican hat filter. Besides, a novel variability filter is proposed to remove strong glint thus reduces false alarm. Kalman filter is used to track the detected targets. A novel track decision algorithm to continue or terminate the track when target disappears is proposed. Prior knowledge of target in Kalman filter is fed forward to an Adaptive 3-D Matched filter to improve the performance. Three sets of real-world infrared image sequences with very different background and target characteristics were used to test the robustness of the multi-modal fusion algorithm. The algorithm performs satisfactorily in all the image sequences. Video clips will also be presented.

关键词： point target fusion algorithm variability filter

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A fusion algorithm: FULLY CONVOLUTIONAL NETWORKS AND STUDENT'S-T MIXTURE MODEL FOR BRAIN MAGNETIC RESONANCE IMAGING SEGMENTATION 25

A FUSION ALGORITHM: FULLY CONVOLUTIONAL NETWORKS AND STUDENT...

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25th IEEE International Conference on Image Processing (ICIP)

作者： Lai, Jiawei Zhu, Hongqing East China Univ Sci & Technol Sch Informat Sci & Engn Shanghai 200237 Peoples R China

ISBN: (纸本)9781479970612

Deep convolutional neural networks (DCNN) are applied widely in image recognition and segmentation. In this paper, a novel algorithm (U-SMM) which incorporates the convolutional neural network U-net and modified Student's-t mixture model (MSMM) is provided. The proposed framework considers the spatial relationships in segmenting medical images with MSMM and then uses U-net to correct the mistake labels made by unsupervised method. Because a few error-segmented regions may be caused by MSMM, the U-net is then applied to learn the features of these regions. In our method, the purpose of U-net is to assist the MSMM in improving the accuracy of segmentation and acquiring rich details in image segmentation tasks. Finally, the proposed framework is evaluated on real MR images with several related supervised and unsupervised methods, and the experimental results confirm the effectiveness of our approach.

关键词： Image segmentation U-net Student's-t mixture models MRI fusion algorithm

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A fusion algorithm Based on Position Difference Filtering and Least Squares Estimate for Dynamic Scene Matching

A Fusion Algorithm Based on Position Difference Filtering an...

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9th International Conference on Computational Intelligence and Security (CIS)

作者： Xia, Zhaohui Wang, Jianyong Yang, Xiaogang Xian Res Inst High Tech Xian 710025 Peoples R China

ISBN: (纸本)9781479925483

For scene matching navigation system, a new fusion algorithm based on Position Difference Filtering (PDF) and Least Squares Estimate (LSE) for dynamic scene matching is proposed to enhance the reliability and matching precision. After the matching results fusion problems for aircraft dynamic scene matching navigation system being analyzed, PDF method is presented to filter the mismatching points and LSE method is adopted to optimum parameter estimation according to the error characteristic of matching position point sequence, then the mismatching points are estimated and the matching position are predicted. It can be seen from the simulation experimental results that the proposed algorithm is feasible and available to eliminate random matching disturbance and the mismatching points for dynamic scene matching navigation system.

关键词： fusion algorithm position difference filter least squares estimate dynamic scene matching

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Recording system and data fusion algorithm for enhancing the estimation of the respiratory rate from photoplethysmogram 37

Recording system and data fusion algorithm for enhancing the...

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37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015

作者： Cernat, Roxana A. Ciorecan, Silvia I. Ungureanu, Constantin Arends, Johan Strungaru, Rodica Mihaela Ungureanu, G. Politehnica University of Bucharest Romania Eindhoven University of Technology Netherlands

ISBN: (纸本)9781424492718

The respiratory rate is a vital parameter that can provide valuable information about the health condition of a patient. The extraction of respiratory information from photoplethysmographic signal (PPG) was actually encouraged by the reported results, our main goal being to obtain accurate respiratory rate estimation from the PPG signal. We developed a fusion algorithm that identifies the best derived respiratory signals, from which is possible to extract the respiratory rate;based on these, a global respiratory rate is computed using the proposed fusion algorithm. The algorithm is qualitatively tested on real PPG signals recorded by an acquisition system we implemented, using a reflection pulse oximeter sensor. Its performance is also statistically evaluated using benchmark dataset publically available from ***. © 2015 IEEE.

关键词： derived respiratory signals fusion algorithm photoplethysmography respiratory rate thermistor

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Research on fusion algorithm with BP Neural Network and Rough Set

Research on Fusion Algorithm with BP Neural Network and Roug...

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6th IEEE Conference on Industrial Electronics and Applications (ICIEA)

作者： Li Wei He Peng-ju Zhang Peng Chen Ming Jiang Li-jun Northwestern Polytech Univ Dept Measurement & Control Technol & Apparat Engn Sch Automat Xian 710072 Peoples R China Republ Polytech Wirless Technol Dev Ctr Singapore Singapore

ISBN: (纸本)9781424487554

Considering that the neural network increases rapidly in complexity and is greatly extended in training time due to the gradually increasing input vectors, a fusion algorithm modified by rough set is proposed to preprocess the inputs before neural network. Firstly, the input sample space is reduced to obtain the new decision table according to attribute significance in rough set. Then the reduced decision table is applied to train the BP neural network until it converges. Finally, the algorithm is used for classification in car mileage level. The classification accuracy of the testing sample is increased by 10% than the traditional BP neural network fusion algorithm. The result shows the modified fusion algorithm is feasible.

关键词： rough set BP neural network attribute significance fusion algorithm

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An airport surface surveillance solution based on fusion algorithm 7

An airport surface surveillance solution based on fusion alg...

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7th International Conference on Electronics and Information Engineering (ICEIE)

作者： Liu Jianliang Xu Yang Liang Xuelin Yang Yihuang Cent S Univ Sch Informat Sci & Engn Changsha 410083 Hunan Peoples R China

ISBN: (数字)9781510610811

ISBN: (纸本)9781510610811

In this paper, we propose an airport surface surveillance solution combined with Multilateration (MLAT) and Automatic Dependent Surveillance Broadcast (ADS-B). The moving target to be monitored is regarded as a linear stochastic hybrid system moving freely and each surveillance technology is simplified as a sensor with white Gaussian noise. The dynamic model of target and the observation model of sensor are established in this paper. The measurements of sensors are filtered properly by estimators to get the estimation results for current time. Then, we analysis the characteristics of two fusion solutions proposed, and decide to use the scheme based on sensor estimation fusion for our surveillance solution. In the proposed fusion algorithm, according to the output of estimators, the estimation error is quantified, and the fusion weight of each sensor is calculated. The two estimation results are fused with weights, and the position estimation of target is computed accurately. Finally the proposed solution and algorithm are validated by an illustrative target tracking simulation.

关键词： airport surface surveillance automatic dependent surveillance-broadcast fusion algorithm Multilateration position estimation

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