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International Applied Computational Electromagnetics Society Symposium (ACES)

作者： Tao Wang Lan Dong Daiyin Zhu Key Laboratory of Radar Imaging and Microwave Photonics Ministry of Education Nanjing University of Aeronautics and Astronautics Nanjing China

Micro synthetic aperture radar (SAR) has become a hot topic because of its small size, low power consumption and light weight. Expanding micro SAR to micro video synthetic aperture radar (vi-SAR) has always been an important research direction. Aiming at the problems of low imaging quality and slow imaging rate of micro SAR, a micro vi-SAR imaging processing system based on multi-core digital signal processor (DSP) is proposed in this paper. The system includes principle of chirp scaling (PCS) module, azimuth Sinc interpolation module, sub image phase Gradient Autofocus (PGA) module. Verified by the measured data of micro SAR, the system can complete the data processing of five single precision floating-point images which are 1K\times 1K in 0. 98s, and finally output the images. The imaging frame rate is up to 5Hz, which is meeting the imaging requirements of real-time vi-SAR.

关键词： Digital signal processors Imaging Signal processing algorithms Radar imaging Streaming media Real-time systems Radar polarimetry

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Unsupervised image Segmentation model based on W Net architecture and Conditional Random Field for Underwater images 7

Unsupervised Image Segmentation model based on W Net archite...

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7th International Conference on Advanced Computing and Communication systems, ICACCS 2021

作者： Saleh, Esra Sorkty Mithun Haridas, T.P. Supriya, M.H. Cochin University of Science and Technology Department of Electronics Kochi India

ISBN: (纸本)9781665405201

Under water imaging has been extensively used in monitoring the marine ecosystems for quite some time. The automated learning systems that are much explored in marine ecosystem are mainly supervised methods. Supervised methods even though require less human intervention, still demands considerable manual effort for the careful design of the dataset. The large amount of labelled and annotated data needed for proper learning, as well as the attention required for designing the ground truth dataset for efficient training, makes the supervised learning approach less attractive, especially in the underwater scenarios. This work explores the possibility of unsupervised learning methods for the analysis of the underwater images using segmentation algorithms, which does not need ground truth annotations and is much more scalable. images and videos from Fish4Knowledge database is utilized for this work to train the unsupervised architecture based on W-Net architecture. The autoencoder architecture is analyzed considering the segmented output from the first half and reconstructed image from the second half using soft N-cut loss and reconstruction loss respectively. Post processing method of Conditional Random Field is also applied for smoothing the initial segmentation. The performance is analyzed using the learning curves and the metrics such as vi, PRI and SC. © 2021 IEEE.

关键词： Random processes

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Entropy and Correlation Coefficients of Neutrosophic and Interval-Valued Neutrosophic Hypersoft Set with application of Multi-Attributive Problems

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Neutrosophic Sets and systems 2022年 49卷 341-356页

作者： Jafar, Muhammad Naveed Saeed, Muhammad Ghani, Tahir Department of Mathematics University of Management and Technology C-II Johar Town Lahore54000 Pakistan Department of Mathematics Lahore Garrison University DHA Phase-VI Sector C Lahore54000 Pakistan

In computational intelligence, machine learning, image processing, neural networks, medical diagnostics, and decision analysis, the ideas of correlation coefficients and entropy have practical applications. By applying hypersoft set (HSS) in neutrosophic environment provides a good model for describing and addressing uncertainties. In statistics, the correlation coefficient between two variables is crucial. Furthermore, the accuracy of the correlation assessment is dependent on data from the discourse set. The main focus of this study, is to develop entropy for (NHSS) and generalized correlation coefficient interval-valued neutrosophic hypersoft-set (IVNHSS). We proposed some theorems on entropy along with algorithms based on correlation and weighted correlation coefficients in the context of NHSs and IVNHSS. The validity and superiority are presented along with application and also comparison is made with existing approaches. © 2022, University of New Mexico. All rights reserved.

关键词： Correlation Coefficients Entropy Fuzziness Hypersoft Set Interval-valued neutrosophic hypersoft set MCDM Neutrosophic hypersoft set Neutrosophic Set Soft Set

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A Data Completion Algorithm Based on Low-Rank Prior Knowledge for Data-Driven Applications

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IEEE Transactions on Network and Service Management 2024年

作者： Tang, Jun Guo, Bing Shen, Yan Garg, Sahil Kaddoum, Georges Hossain, M. Shamim Sichuan University College of Computer Science Chengdu China Chengdu University of Information Technology School of Computer Science Chengdu China École de Technologie Supérieure Electrical Engineering Department MontréalQCH3C 1K3 Canada Chitkara University Institute of Engineering and Technology Chitkara University Centre for Research Impact and Outcome Punjab Rajpura140401 India Lebanese American University Artificial Intelligence and Cyber Systems Research Center Beirut03797751 Lebanon King Saud University College of Computer and Information Sciences Department of Software Engineering Riyadh12372 Saudi Arabia

Low rank tensor ring based data recovery algorithms have been widely used in data-driven consumer electronics to recover missing data entries in the collecting data pre-processing stage for providing stable and reliable service. However, traditional recovery methods often fail to utilize the abundant prior knowledge of data and the non-local self-similarity of the data, thus leading to the failure to effectively capture the spatial relationships within high-dimensional data to recover them accurately. To address these problems, we present a novel Non-local Self-similarity and Low-rank Prior Knowledge based tensor ring completion method. Firstly, we incorporate the BM3D denoising operator within a Plug-and-Play framework to exploit the self-similarity in the data. Then a logarithmic determinant function is integrated to distinguish singular values in the cyclic unfolding matrix of the tensor and adopts a tensor ring completion approach based on weighted nuclear norms. Finally, in order to evaluate the effectiveness of our proposed method, we conducted a series of experiments by using the missing image dataset and the missing traffic data dataset respectively, and the experimental results show that our method achieves the highest level in terms of data recovery accuracy. © 2024 IEEE.

关键词： Data assimilation

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image denoising with bank filters using the maximum likelihood estimation 5

Image denoising with bank filters using the maximum likeliho...

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Conference on Computational Imaging V

作者： Bezuglov, D. Voronin, V. Russian Customs Acad Rostov Branch 20 Budyonnovsky Ave Rostov Na Donu 344002 Russia Moscow State Univ Technol STANKIN Ctr Cognit Technol & Machine Vis Vadkovsky 1 Moscow 127055 Russia Don State Tech Univ Lab Math Methods Image Proc & Intelligent Comp Vi Rostov Na Donu Russia

ISBN: (纸本)9781510635692

Recently, systems of intelligent image processing have been intensively developing. When solving problems of high complexity, modern methods of technical vision are required to increase the efficiency of the digital image processing process with the variability of the working scene, heterogeneity of objects, and interference. One of the trends in the development of modern information technologies is the development of highly efficient methods and algorithms for analyzing signals and images with background noises. When constructing highly-effective techniques and algorithms for image denoising, an a priori knowledge of the characteristics of distorting interference is required. In practice, in most cases, such information is missing. In this paper, we develop a new image denoising method with bank filters using the maximum likelihood estimation. We propose a new approach to using a set of heterogeneous digital image filters, such as a median filter, a Gabor filter, a non-local average filter, a spline filter, a wavelet filter, and others. The feasibility of this approach is determined by the fact that, as a rule, when considering the filtering process, a Gaussian character of the noise distribution density is assumed. Moreover, the effectiveness of various filtering methods on real images recorded against the background of noise will be different. This is due to the fact that under real observation conditions, the noise distribution density may differ from the Gaussian one. This explains the difference in the qualitative filtering characteristics of the same image by different filters. Experimental studies have shown the operability and high efficiency of the developed method, which allows improving the quality of image filtering.

关键词： image denoising median filter Gabor filter wavelet filter filter bank maximum likelihood estimation

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The Automated Technology for Converting Drawing and Design Paper-Based Documentation into Electronic 3D Model of an Object 6

The Automated Technology for Converting Drawing and Design P...

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6th International Conference on Information Technology and Nanotechnology (IEEE ITNT)

作者： Vasin, Dmitry Gromov, Vladimir Romensky, Sergey Rotkov, Sergey Lobachevsky State Univ Nizhny Novgorod Ctr Informat & Intelligent Informat Technol Nizhnii Novgorod Russia Nizhny Novgorod State Univ Architecture & Civil E Dept Engn Geometry Comp Graph & Comp Aided Design Nizhnii Novgorod Russia

ISBN: (纸本)9781728170411

We propose the original automated information technology for transformation of paper archives of drawing and design documentation into electronic 3D model of an object for CALS and BIM ideologies of designing and manufacturing of an object. The technology assumes the full automated cycle of processing of projective kinds from initial paper drawings to electronic frame 3D model of an object. Original models of representation and algorithms of solving the given problem are proposed.

关键词： CALS BIM 3D model CAD systems

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Unsupervised image Segmentation model based on W Net architecture and Conditional Random Field for Underwater images

Unsupervised Image Segmentation model based on W Net archite...

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International Conference on Advanced Computing and Communication systems (ICACCS)

作者： Esra Sorkty Saleh T.P. Mithun Haridas M.H. Supriya Cochin University of Science and Technology Kochi India

关键词： Training Measurement image segmentation Analytical models Databases Ecosystems Computer architecture

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Monolithic-3D Inference Engine with IGZO Based Ferroelectric Thin Film Transistor Synapses

TechRxiv

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TechRxiv 2022年

作者： De, Sourav Lederer, Maximilian Raffel, Yannick Lehninger, David Thunder, Sunanda Jank, Michael P.M. Ali, Tarek Kämpfe, Thomas Seidel, Konrad Sanctis, Shawn Fraunhofer-Institut für Photonische Mikrosysteme IPMS Center Nanoelectronic Technologies Dresden Germany Fraunhofer-Institut für Integrierte Systeme und Bauelementetechnologie Erlangen Germany

Instigated by the plethora of data generated by edge devices and IoT devices, machine learning has become the de facto choice of everyone for solving many tasks. Applications such as intelligent healthcare monitoring systems, smart watches, or autonomous cars require real-time processing of the data or image, which is done by machine learning algorithms with higher efficiency than humans. There are two possible methods for artificial intelligence-1. non-von-Neumann hardware-based implementation of neural networks 2. traditional computer science-based approach for neural networks or traditional von Neumann architecture-based implementation of neural networks The standard von-Neumann performance of neural networks, where the memory and computation parts are segregated, suffers from severe latency with an increasing number of edge devices. However, the multitude of edge devices used in our daily life imposes strict restrictions on latency, device area, and power consumption for hardware. Therefore, we need to take the route beyond the CMOS-based mixed-signal implementation of neural networks, where the memory bandwidth is not limited by the quintessential von Neumann architecture. The primary motivation of present-day research on the non-von-Neumann computing architecture is to build dedicated hardware modules for implementing low-power, fast-computing units without affecting the recent trend of scaling. This chapter focuses on amorphous indium-gallium-zinc-oxide (α-IGZO) based and their system-level applications. Back-end-of-line (BEoL) compatible indium IGZO-based multibit one-time programmable (OTP) ferroelectric thin film transistors (FeTFT) with lifelong retention capability were fabricated. The maximum temperature of the entire fabrication process was limited to 350oC. The gate-stack engineering by varying the thickness ratio of ferroelectric hafnium zirconium oxide (HZO) and IGZO layer fomented excellent data-retention capability and one-time programming propert

关键词： II-vi semiconductors

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image processing and machine learning applications in mining industry: Mine 4.0 3

Image processing and machine learning applications in mining...

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3rd International Conference on Intelligent systems and Advanced Computing Sciences, ISACS 2019

作者： Ouanan, Hamid Abdelwahed, El Hassan National School of Applied Sciences Sultan Moulay Slimane University Beni Mellal Morocco CSEHS Mohammed VI Polytechnic University Marrakesh Morocco

ISBN: (纸本)9781728148137

Recently, image processing (IP) and Machine learning (ML) algorithms have been successfully used in a wide variety of industry sectors. In this paper, we first provide mining engineers with the state of the art about IP and ML applications in the mining industry. furthermore, we propose a real time application for froth image analysis in the context of mineral processing. Finally, we propose some future directions, including suggestions on mining data collection and development of an exploration tool based on IP and ML algorithms by taking advantage of cloud computing technology to analyze geoscience data in order identify target areas with high prospectively potential. © 2019 IEEE.

关键词： Machine learning

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Industrial monocular multispectral 3D-imager

Industrial monocular multispectral 3D-imager

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image Sensing Technologies: Materials, Devices, systems, and Applications vi 2019

作者： Rosenberger, M. Golomoz, A. Celestre, R. Zhang, C. Fütterer, R. Notni, G. Technische Universität Ilmenau Dept. Mechanical Engineering Group for Quality Assurance and Industrial Image Processing Gustav Kirchhoff Pl.2 Ilmenau98693 Germany

ISBN: (纸本)9781510626256

This paper presents the latest developments on filter-wheel based multispectral imaging systems as well as their extension to making 3D images. The system, capable of producing high spatial resolution images on a spectrum spanning from 400nm to 1050nm (in 12 steps of 50nm (configurable) with 50nm or less bandwidth) can be used, without hardware change. To produce 3D image stacks where the height resolution is given by the numerical aperture of the optics used and the reproducibility of the image plane moving motor is also possible. This paper introduces the reader to spectral imaging and to 3D measurement techniques. The main parameters and relevant publications of/about the industrial monocular multispectral 3D-imager are then presented. Correction of chromatic aberration on filter wheel system, a key idea for 3D image reconstruction, is revised. 3D imaging capabilities of the system as well as proper calibration are introduced. Selected applications and algorithms are presented towards to the end of the paper. © 2019 SPIE.

关键词： Spectroscopy

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