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Research on synthetic aperture radar recognition method based on deep learning

Research on synthetic aperture radar recognition method base...

引用

2024 International Conference on algorithms, High Performance Computing, and Artificial Intelligence, AHPCAI 2024

作者： Hua, Zhendong Wang, Haifeng Wang, Haoxin Chinese Flight Test Establishmen Xi’an China

ISBN: (纸本)9781510685840

Target recognition in SAR images is a key issue in remote sensing image processing, which is widely used in many fields. Traditional recognition methods face many challenges due to the complexity of SAR images. In this paper, we propose an improved method based on GoogLeNet and improved YOLOV5 algorithm to cope with the limitations of MSTAR dataset. In this paper, GoogLeNet is introduced to improve the performance of target recognition in complex backgrounds, and its unique module improves the efficiency while reducing the parameters, which is especially suitable for handling small targets and complex textures in SAR images. Meanwhile, YOLOV5 is improved to enhance the detection accuracy and reduce the computational complexity. The effectiveness and superiority of the method is verified through experiments on the MSTAR dataset. © 2024 SPIE.

关键词： Synthetic aperture radar Target detection Convolution Target recognition Education and training detection and tracking algorithms Feature extraction Image processing Performance modeling Neck

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HIGH-SPEED VLSI WORKPIECE POSITION MEASUREMENT USING NORMALIZED 2D-CORRELATION

HIGH-SPEED VLSI WORKPIECE POSITION MEASUREMENT USING NORMALI...

引用

20th Annual SPIE Conference on Machine Vision Applications in Industrial Inspection

作者： ROTHACHER, F FELBER, N FED INST TECHNOL INTEGRATED SYST LABZURICHSWITZERLAND

ISBN: (纸本)0819414786

For workpiece recognition, the image processing unit of an assembly robot must be fast and reliable. To improve an already existing system, we implemented an ASIC for real-time image correlation from a standard video image based on an investigation of several algorithms for 2D grayscale image correlation. The architecture contains four parallel multipliers and uses a three- level pipelining schema. The ASIC, which is realized in a standard and macrocell technique, achieves a sustained performance of 16 X 10⁶ MAC/s. A speed-up factor of 12 compared to a DSP56116 implementation at the same clock speed is obtained.

关键词： Video Clocks Digital signal processing Very large scale integration Correlation function CCD cameras detection and tracking algorithms Image processing Reflection System integration

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An attention mechanism based infrared imaging detail enhancement algorithm design and implementation with FPGA

An attention mechanism based infrared imaging detail enhance...

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2024 Applied Optics and Photonics China: Laser Technology and Applications, AOPC 2024

作者： Liu, Wan-Cheng Yang, Yi-Ning Wang, Jinjin National Key Laboratory of Electromagnetic Space Security Tianjin China

ISBN: (数字)9781510687745

ISBN: (纸本)9781510687738

This article proposes an adaptive infrared image detail enhancement algorithm guided by visual attention map for the issue that the output image of infrared detection equipment features concentrated gray value and low contrast. The algorithm separates the base layer and the detail layer via edge-preserving filters such as guided filtering, compresses the dynamic range of the base layer image, and adaptively enhances the detail layer image. Subsequently, the low contrast infrared image is reconstructed by the base layer after dynamic range compression and the detail layer after detail enhancement. Finally, the algorithm is deployed on the FPGA platform, which significantly improves the image contrast and meets the real-time requirements of the mid-wave infrared 640×512 array detection system. © 2024 SPIE.

关键词： Image enhancement Image filtering Tunable filters Infrared imaging Field programmable gate arrays Infrared radiation detection and tracking algorithms Visualization Image processing Windows

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DIAGNOSIS OF HEPATITIS BY USE OF NEURAL-NETWORK LEARNING

DIAGNOSIS OF HEPATITIS BY USE OF NEURAL-NETWORK LEARNING

引用

5th International Conference on Applications of Artificial Neural Networks

作者： FAN, HQ ZHANG, QZ FIRST EPIDEM HOSP SHENYANG 110006PEOPLES R CHINA

ISBN: (纸本)0819415472

An attempt is made to find a new way for better diagnosis of hepatisis through application of artificial neural network theory. Learning from a given sample set, the neural network is used to establish a nonlinear mapping between various factors, such as symptoms, signs, and laboratorial experiments, and diagnosis of hepatisis. It is proved that the used network and values of weight after learning are available to the identification of equivalent class of a new pattern of hepatisis. In this paper, the knowledge learning and learning algorithms used in diagnosis are mainly discussed, an optimal generalization algorithm based on the error decrease algorithm and used to train multilayer feedforward is presented; meanwhile, the application results and their effectiveness are introduced.

关键词： Neural networks Neurons detection and tracking algorithms Error analysis Rule based systems Artificial neural networks Computing systems Data hiding Evolutionary algorithms Pattern recognition

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Spectrum spreading algorithm for efficient embedding of watermarks

Spectrum spreading algorithm for efficient embedding of wate...

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4th Conference on Mathematics of Image and Data Coding, Compression, and Encryption

作者： Yeo, IK Kim, HJ Kangwon Natl Univ Dept Control & Instrumentat Engn Chunchon South Korea

ISBN: (纸本)0819441899

Time-domain and frequency-domain spreading algorithms are presented in this paper. However, detection algorithm does not rely on correlation method, but based on patchwork method. Time-domain algorithm can survive translation and clipping attacks. Frequency-domain algorithm is robust against compression attack. Embedding and detection functions are presented. Simulation results show the effectiveness of the algorithms.

关键词： Digital watermarking Error analysis Image processing detection and tracking algorithms Image compression Signal to noise ratio Signal detection Computer simulations Image quality Interference (communication)

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Time Series Anomaly detection Using LSTM and Attention 4

Time Series Anomaly Detection Using LSTM and Attention

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4th International Conference on Internet of Things and Smart City, IoTSC 2024

作者： Li, Guangyao Dai, Yawen School of Information Engineering Wuhan University of Technology Wuhan430070 China Faculty of Science Wuhan University of Technology Wuhan430070 China

ISBN: (纸本)9781510681767

Time series data anomaly detection is to identify observations or patterns in some chronologically ordered points which are significantly inconsistent with expected patterns or normal behavior. These patterns may indicate unexpected events, unusual behavior, failures, or other unusual conditions in the system. Time series anomaly detection has important applications in many fields, including industry, finance, medical care, etc. We designed a time series anomaly detection algorithm using LSTM(Long Short-Term Memory) and attention. By adding an attention layer after the LSTM network, the network can pay more attention to more relevant features in the input multivariate time series, thereby improving accuracy and recall. In the data preprocessing process, the decision tree algorithm is used on the original data set to remove features that have little impact on the anomaly detection results, so as to reduce the computational complexity of anomaly detection, and improve the efficiency of anomaly detection. Experiments on the industrial time series data set SWaT data set show that the LSTM-Attention model proposed in this article is better to the basic LSTM network in terms of precision, recall, F1score and other indicators, and achieves good time series data anomaly detection results. © 2024 SPIE.

关键词： Data modeling Education and training Decision trees Performance modeling Process modeling Statistical modeling Data processing detection and tracking algorithms Deep learning Mathematical optimization

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Moving target detection in over-the-horizon radar using adaptive chirplet transform

Moving target detection in over-the-horizon radar using adap...

引用

Conference on Wavelet and Independent Component Analysis Applications IX

作者： Wang, GY Xia, XG Root, BT Chen, VC Univ Delaware Dept Elect & Comp Engn Newark DE 19716 USA

ISBN: (纸本)081944488X

In over-the-horizon radar (OTHR) moving target detection, the signal to clutter ratio (SCR) is low. One method to detect a moving target is to first reject the clutter and improve the SCR before the detection, such as the adaptive Fourier transform developed by Root when a target moves uniformly. When a target does not move uniformly, the Fourier based techniques for the target detection including super resolution techniques may not work well. In this paper, we replace the Fourier transform by the adaptive chirplet transform in the Doppler processing in OTHR when a target moves non-uniformly.

关键词： Target detection Doppler effect Signal detection Fourier transforms Radar detection and tracking algorithms Radar signal processing Darmstadtium Signal processing Electronic filtering

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Communication theory framework for document recognition

Communication theory framework for document recognition

引用

Document Recognition

作者： Kopec, Gary E. Chou, Philip A. Xerox Palo Alto Research Ctr. (United States)

ISBN: (纸本)081941476X

Document image decoding (DID) is a recently proposed generic framework for document recognition that is based on an explicit communication theory view of the processes of document creation, transmission, and interpretation. DID views a document recognition problem as containing four elements - a message (information) source, an encoder (formatter and renderer), a noisy channel (e.g., printer, scanner) and an image decoder (recognizer). Application of DID to a particular recognition problem involves developing stochastic models for the source, encoder, and channel processes. The DID approach to modeling is based on the use of stochastic attributed context-free grammars. DID supports an approach to image decoding that has as the kernel of the method an informed best-first search algorithm, called the iterated complete path (ICP) algorithm, that is similar to branch-and bound and related heuristic search and optimization techniques. The inputs to the decoder generator are a Markov source model and values for channel parameters. The generator creates the necessary computation schedules and outputs an optimized in-line C program that implements the decoder. The customized decoder program is then compiled, linked with a support library and used to decode images.

关键词： Stochastic processes Communication theory Image processing Computer programming detection and tracking algorithms Data modeling Image transmission Optimization (mathematics) Printing Scanners

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Progress in automatic reading of complex typeset pages

Progress in automatic reading of complex typeset pages

引用

Imaging Workstations 1989

作者： Vincent, Philippe INOVATIC 3 Avenue du Centre Saint Quentin en Yvelines cédex78282 France

For a long time, automatic reading has been limited to optical character recognition. one year ago, except for one high end product, all industrial software or hardware products where limited to the reading of mono-column texts without images. This does not correspond to real life needs. In a current, company, pages which need to be transformed into electronic form are not only typewritten pages, but also complex pages from professional magazines, technical manuals, financial reports and tables, administrative documents, various directories, lists of spare parts etc... The real problem of automatic reading is to transform such complex paper pages including columns, images, drawings, titles, footnotes, legends, tables, occasionally in landscape format, into a computer text file without the help of an operator. Moreover, the problem is to perform this operation at an economical cost with limited computer resources in terms of processor and memory.

关键词： Imaging systems Document imaging Image segmentation Mathematical modeling Optical character recognition Algorithm development detection and tracking algorithms Image processing Software Image classification

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Zero-shot industrial anomaly detection and localization via reweighted density estimation 9

Zero-shot industrial anomaly detection and localization via ...

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

作者： Fan, Wei Shen, Yaomin Zuo, Jiali Dept. Computer Science and Technology Jiangxi Normal University Nan chang China

ISBN: (纸本)9781510683303

To achieve high quality industrial Anomaly detection (AD) is difficult as there are no anomalous samples in the training set and one need to treat the defective region in the test images as outliers. Recently, some researchers even propose to perform the AD in a zero-shot manner. The algorithm is required to predict the defective state of each test image without the training phase. Surprisingly, the pioneering work has achieved relatively high accuracy in this challenging scenario thanks to the smart low density assumption of the anomalous patches in the feature space. In this paper, we propose to improve the successful zero-shot method by introducing the dynamic density estimation of the patch features. The experiment results illustrate a significant performance gain in all the involved 4 metrics for anomaly detection or localization. © 2024 SPIE.

关键词： detection and tracking algorithms Feature extraction Histograms Education and training Defect detection Statistical modeling

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