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检索条件"主题词=Detection and tracking algorithms"

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The BP neural network microgrid fault diagnosis method based on optimisation of pelican algorithm

The BP neural network microgrid fault diagnosis method based...

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2024 International Conference on Automation Control, Algorithm, and Intelligent Bionics, ACAIB 2024

作者： Sun, Mingze Guo, Yanbing Hou, Yongkang Shanghai Dianji University School of Mechanical Shanghai201306 China College of Ocean Science and Engineering Institute of Marine Materials Science and Engineering Shanghai Maritime University Shanghai201306 China Shanghai Dianji University School of Business Shanghai201306 China

ISBN: (纸本)9781510682597

In this study, a fault diagnosis method combining the Pelican algorithm and BP neural network is proposed for improving the fault diagnosis accuracy and efficiency of microgrid systems. Pelican algorithm is a new optimisation algorithm developed in recent years, which can effectively optimise the weights and deviations of BP neural networks. Based on this characteristic, the Pelican algorithm is used to process the data of the actual microgrid system, and compared and analysed with the traditional BP neural network and RNF neural network. The experimental results show that the BP neural network optimised by the Pelican algorithm exhibits higher accuracy and robustness in microgrid fault diagnosis, which provides an important support for the reliability of microgrid systems. © 2024 SPIE.

关键词： Neural networks Evolutionary algorithms Mathematical optimization Data modeling Education and training Algorithm development Computer simulations detection and tracking algorithms Diagnostics

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Front matter: volume 10988 29

Front matter: volume 10988

引用

Automatic Target Recognition XXIX 2019

作者： Hammoud, Riad I. Overman, Timothy L.

This PDF file contains the front matter associated with SPIE Proceedings Volume 10988, including the Title Page, Copyright Information, Table of Contents, Author and Conference Committee lists.

ISBN: (纸本)9781510626416

This PDF file contains the front matter associated with SPIE Proceedings Volume 10988, including the Title Page, Copyright Information, Table of Contents, Author and Conference Committee lists.

关键词： Automatic target recognition Machine learning Computing systems detection and tracking algorithms Algorithm development Analytical research Image segmentation Data modeling Remote sensing Target recognition

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Face recognition through pose estimation and fringe-adjusted joint transform correlation

Face recognition through pose estimation and fringe-adjusted...

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Conference on Optical Pattern Recognition XIII

作者： AlSamman, A Alam, MS Univ New Orleans Dept Elect & Comp Engn New Orleans LA 70146 USA

ISBN: (纸本)0819444847

In this paper we describe a simple pose estimation based optoelectronic system for the recognition of facial images. The pose estimation described herein is a simple digital algorithm that is used to replace the composite image generation techniques while maintaining a low interclass cross correlation. The optoelectronic fringe adjusted join transform correlator (FJTC) is then used to provide correlation. A description of the optoelectronic system and the entire process is presented. In addition, simulation result and comparison to SDF based recognition are provided to prove the effectiveness of the proposed system.

关键词： Composites Databases detection and tracking algorithms Facial recognition systems Fourier transforms Image processing Joint transforms Optoelectronics Head Optical correlators

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Estimation of the short-wave incoming radiation from AVHRR data on the Arctic Ocean

Estimation of the short-wave incoming radiation from AVHRR d...

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Conference on Remote Sensing of the Ocean and Sea Ice 2000

作者： Ananasso, C Santoleri, R Marullo, S Nardino, M Hartmann, J CNR Ist Fis Atmosfer Rome Italy

ISBN: (纸本)0819438286

An empirical method to estimate the solar incoming radiation has been improved using AVHRR (Advanced Very High Resolution Radiometer)-NOAA14 data in the framework of the ARTIST (Arctic Radiation and Turbulence Interaction Study) experiment. This method, using several bulk formulas, gives an estimation of the incoming solar radiation and results are compared with the surface-based and aircraft-based measurements. The first step of the method is the development of a cloud detection algorithm for the area and for the period of interest. The area is the Arctic Ocean near the Svalbard Islands and the period is from 15 March to 16 April 1998, the transition period from winter to spring and in this particular case from the Polar Night to a period of quite normal insolation. Several bulk formulas, right for the Polar condition, are tested comparing the estimate insolation fluxes with the direct measurements made with a pyranometr mounted aboard the Polar2 aircraft and an other pyranometer at the research base at Ny-Alesund. The comparison could define the best parameterization for the available data.

关键词： Clouds Solar radiation Satellites detection and tracking algorithms Algorithm development Environmental sensing Error analysis Visualization Meteorological satellites Satellite imaging

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Change detection in monochromatic imagery

Change detection in monochromatic imagery

引用

Applications of Artificial Intelligence VII 1989

作者： Davis, Larry S. Harwood, David A. Chen, Ling Tony Hsu, Diane Computer Vision Laboratory University of Maryland College ParkMD20742 United States

An important application of vision in aerial reconnaissance is the detection and classification of changes between images of the same scene taken at different times. There are a variety of factors that make this an exceedingly difficult problem: 1) The images are ordinarily taken from (slightly) different vantage points. If the images are taken at sufficiently high altitudes, then the images can, in principle, be registered by a single global coordinate transformation. Otherwise (and this is often the case) the images must be treated as a stereo pair, and the corresponding disparity field must be computed in order for the images to be compared.

关键词： Image segmentation Sun Evolutionary algorithms Artificial intelligence Clouds Image enhancement Reflectivity detection and tracking algorithms Image registration Sensors

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Design of online detection algorithm for bolt fastening state in substation based on deep learning 4

Design of online detection algorithm for bolt fastening stat...

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4th International Conference on Image Processing and Intelligent Control, IPIC 2024

作者： Guo, Zhigang Li, Zhichao Yang, Wei Yu, Peiyong Zhao, Xiaolong Super High Voltage Company of State Grid Heilongjiang Electric Power Co. Ltd. Harbin150090 China

ISBN: (纸本)9781510682313

As the core component of the power system, the normal operation of the substation is very important to the reliability of the power supply. As one of the key elements to connect substation equipment, the maintenance of the bolt fastening state has an important impact on the safety and stability of equipment. The purpose of this study is to propose an algorithm based on deep learning, which is used to detect the fastening state of substation bolts in real time to ensure the normal operation and maintenance of equipment. In this study, we collected a large number of substation bolt state data and designed a deep learning model. Firstly, we preprocessed the data with Gramian Angular Field (GAF) and Piecewise Aggregate Approximation (PAA). Then, we put forward a diagnosis model of the acoustic emission signal of substation bolts based on two-dimensional time series and Attention Mechanism (AM), and then use this model to capture the time series information of bolt state. The experimental results show that after 100 iterations, the diagnostic accuracy of the model has reached the highest, with an average accuracy of about 98%. Our deep learning algorithm can highly accurately identify the fastening state of bolts, which provides an effective guarantee for the safety and reliability of substations, and also has the ability to monitor in real-time. © 2024 SPIE.

关键词： Deep learning Data modeling Acoustic emission detection and tracking algorithms Education and training Windows Safety Visual process modeling Matrices Reliability

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Design of an intelligent product recognition system based on image correction 9

Design of an intelligent product recognition system based on...

引用

9th International Symposium on Advances in Electrical, Electronics, and Computer Engineering, ISAEECE 2024

作者： Huang, Qihao Wang, Dan Chen, Yunhao College of Mechanical and Electrical Engineering Guangdong University of Science and Technology Guangdong Dongguan523083 China

ISBN: (纸本)9781510683303

In the use of barcodes for commodity identification, the barcode recognition of non-planar commodities has the problem of a high error rate. Hence, designing commodity intelligent systems based on image correction was carried out. The proposed fisheye-image aberration correction technique was used to eliminate the aberrations in the image and improve the barcode recognition accuracy. At the same time, it was combined with the hardware system to recognize commodities rapidly. Through experiments, it is verified that the system has the function of commodity recognition and can improve the accuracy of non-planar commodity barcode recognition. © 2024 SPIE.

关键词： Intelligence systems Image processing Aberration correction Image restoration Design Distortion detection and tracking algorithms Displays Spherical lenses Visualization

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Improved the lightweight part identification method of YOLOv5 4

Improved the lightweight part identification method of YOLOv...

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4th International Conference on Artificial Intelligence and Electromechanical Automation, AIEA 2023

作者： Qin, Qi Zhao, Li-Gang Yuan, Jun-Tao School of Mechanical Engineering Jiangsu University of Science and Technology Zhenjiang212100 China Jiangsu Provincial Key Laboratory of Advanced Manufacturing for Marine Mechanical Equipment Jiangsu University of Science and Technology Zhenjiang212100 China

ISBN: (纸本)9781510666412

Aiming at the defects of the existing part recognition methods in the industrial production process when identifying small and dense parts, and the problem that the number of model parameters and large volume are difficult to deploy on the mobile platform, an improved YOLOv5 lightweight part target recognition model is proposed. On the basis of the YOLOv5 model, the Ghost module is first used to replace the backbone network to reduce the number of parameters of the model. Secondly, a SPP_F feature pyramid structure is constructed to speed up the training speed of the model and strengthen the ability of the model to extract information. Remove the detection layer for large target scales, thereby speeding up model training and detection;Finally, the GIOU function in the YOLOv5 model is replaced with the Alpha-SIOU function to improve the positioning accuracy of the bounding box. Experimental results show that the average accuracy (mAP) of the improved model reaches 99.5%, and the volume only accounts for 3.2MB, which is 35% faster than the original YOLOv5 model, reducing hardware costs and meeting the needs of deployment in low-computing equipment. © 2023 SPIE.

关键词： detection and tracking algorithms Convolution Data modeling Feature extraction Performance modeling Object detection Target detection Target recognition Education and training Image processing

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Rapid prototyping of update algorithm of Discrete Fourier Transform for real-time signal processing

Rapid prototyping of update algorithm of Discrete Fourier Tr...

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11th Conference on Automatic Target Recognition

作者： Kakad, YP Sherlock, BG Chatapuram, KV Bishop, S Univ N Carolina Dept Elect & Comp Engn Charlotte NC 28223 USA

ISBN: (纸本)0819440744

An algorithm is developed in the companion paper [I], to update the existing Discrete Fourier Transform (DFT) to represent the new data series that results when a new signal point is received. Updating the DFT in this way uses less computation than directly evaluating the DFT using the FFT algorithm. This reduces the computational order by a factor of log2 N. The algorithm is able to work in the presence of data window function, for use with rectangular window, the split triangular, Hanning, Hamming, and Blackman windows. In this paper, a hardware implementation of this algorithm, using Field Programmable Gate Array (FPGA) technology, is outlined. Unlike traditional fully customized VLSI circuits, FPGAs represent a technical break through in the corresponding industry. The FPGA implements thousands of gates of logic in a single Integrated Circuit (IC) chip and it can be programmed by users at their site in a few seconds or less depending on the type of device used. The risk is low and the development time is short. The advantages have made FPGAs very popular for rapid prototyping of algorithms in the area of digital communication, digital signal processing, and image processing. Our paper addresses the related issues of implementation using hardware descriptive language in the development of the design and the subsequent downloading on the programmable hardware chip.

关键词： Field programmable gate arrays Signal processing Fourier transforms Rapid manufacturing Algorithm development Clocks Logic detection and tracking algorithms Data communications Very large scale integration

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Staged multi-target tracking and matching algorithm combined with depth estimation information

Staged multi-target tracking and matching algorithm combined...

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2024 International Conference on Image, Signal Processing, and Pattern Recognition, ISPP 2024

作者： Jia, Yunhua Zhou, Chengjiang Yunnan Normal University School of Information Kunming650500 China Pattern Recognition and Artificial Intelligence Laboratory Kunming650500 China

ISBN: (纸本)9781510680425

As the field of artificial intelligence progresses, multi-target tracking, one of the advanced visual tasks of computer vision, has developed *** present, as multi-target tracking technology gradually matures, related scientific research results are slowly appearing in our daily lives, bringing more powerful help to our ***, the precision of multi-target tracking faces significant constraints, mainly attributed to factors like occlusion and interference from the *** to reduce the constraints of occlusion and other factors on the accuracy of multi-target *** this paper, we propose a staged multi-target tracking and matching algorithm that combines depth estimation *** using the depth estimation information of targets in the scene, combined with the proposed staged matching algorithm improves the precision of the algorithm for multi-target tracking. © 2024 SPIE.

关键词： detection and tracking algorithms Ablation Algorithm development Data modeling Computer vision technology Sensors Video

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