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Meta-Learning Multi-Scale Radiology Medical Image Super-Resolution

Computers, Materials & Continua 2023年第5期75卷 2671-2684页

作者： Liwei Deng Yuanzhi Zhang Xin Yang Sijuan Huang Jing Wang Heilongjiang Provincial Key Laboratory of Complex Intelligent System and Integration School of AutomationHarbin University of Science and TechnologyHarbin150080HeilongjiangChina Department of Radiation Oncology Sun Yat-sen University Cancer CenterState Key Laboratory of Oncology in South ChinaCollaborative Innovation Center for Cancer MedicineGuangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and TherapyGuangzhou510060GuangdongChina Faculty of Rehabilitation Medicine Biofeedback LaboratoryGuangzhou Xinhua UniversityGuangzhou510520GuangdongChina

High-resolution medical images have important medical value,but are difficult to obtain *** by hardware equipment and patient’s physical condition,the resolution of directly acquired medical images is often not ***,many researchers have thought of using super-resolution algorithms for secondary processing to obtain high-resolution medical ***,current super-resolution algorithms only work on a single scale,and multiple networks need to be trained when super-resolution images of different scales are *** definitely raises the cost of acquiring high-resolution medical ***,we propose a multi-scale superresolution algorithm using *** algorithm combines a metalearning approach with an enhanced depth of residual super-resolution network to design a meta-upscale *** meta-upscale module utilizes the weight prediction property of meta-learning and is able to perform the super-resolution task of medical images at any ***,we design a non-integer mapping relation for super-resolution,which allows the network to be trained under non-integer magnification *** to the state-of-the-art single-image super-resolution algorithm on computed tomography images of the pelvic *** meta-learning multiscale superresolution algorithm obtained a surpassing of about 2%at a smaller model *** on different parts proves the high generalizability of our ***-scale super-resolution algorithms using meta-learning can compensate for hardware device defects and reduce secondary harm to patients while obtaining high-resolution medical *** can be of great use in imaging related fields.

关键词： Super resolution deep learning meta learning computed tomography

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Logarithm Radon-Fourier transform for high speed small target detection with atmospheric resistance effect

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Digital Signal Processing: A Review Journal 2025年 165卷

作者： Sun, Difeng Xu, He Wu, Zutang Li, Jin Wu, Youcao Li, Jianbing State Key Laboratory of Complex Electromagnetic Environmental Effects on Electronics and Information System College of Electronic Science and Technology National University of Defense Technology Changsha410073 China National Key Laboratory of Intense Pulsed Radiation Simulation and Effect Northwest Institute of Nuclear Technology Xi'an710024 China Academy of Military Science of the People's Liberation Army Beijing100071 China

Detecting high-speed, small targets in air is challenging due to their complex non-linear motion model and range migration effects. Traditional finite order polynomial models often fail to account for atmospheric drag accurately. This paper introduces a logarithmic relationship between range and time to model this motion, employing the Logarithmic Radon-Fourier Transform (LRFT) for accurately compensating the envelope and phase migration over extended accumulation periods. It offers both the ergodic search method and the fast implementation method for solving LRFT, along with a theoretical analysis of lobe location and amplitude. Simulation results indicate that compared with traditional RFT-based methods, LRFT improves accumulation gain, enhances the main lobe's relative amplitude over sidelobes, and offers better detection performance in noisy environments. It provides more accurate recovery of target motion and improved target distinction capabilities. These benefits over traditional methods are especially evident when the product of the attenuation coefficient α, the initial velocity v0, and the total coherent accumulation time TM exceeds a specific threshold. © 2025 Elsevier Inc.

关键词： Fast Fourier transforms

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Lightweight hybrid visual-inertial odometry with closed-form zero velocity update

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Chinese Journal of Aeronautics 2020年第12期33卷 3344-3359页

作者： QIU Xiaochen ZHANG Hai FU Wenxing School of Automation Science and Electrical Engineering Beihang UniversityBeijing 100191China Science and Technology on Aircraft Control Laboratory Beijing 100191China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing 100074China

Visual-Inertial Odometry(VIO) fuses measurements from camera and Inertial Measurement Unit(IMU) to achieve accumulative performance that is better than using individual *** VIO is an extended Kalman filter-based solution which augments features with long tracking length into the state vector of Multi-State Constraint Kalman Filter(MSCKF). In this paper, a novel hybrid VIO is proposed, which focuses on utilizing low-cost sensors while also considering both the computational efficiency and positioning precision. The proposed algorithm introduces several novel contributions. Firstly, by deducing an analytical error transition equation, onedimensional inverse depth parametrization is utilized to parametrize the augmented feature *** modification is shown to significantly improve the computational efficiency and numerical robustness, as a result achieving higher precision. Secondly, for better handling of the static scene,a novel closed-form Zero velocity UPda Te(ZUPT) method is proposed. ZUPT is modeled as a measurement update for the filter rather than forbidding propagation roughly, which has the advantage of correcting the overall state through correlation in the filter covariance matrix. Furthermore, online spatial and temporal calibration is also incorporated. Experiments are conducted on both public dataset and real data. The results demonstrate the effectiveness of the proposed solution by showing that its performance is better than the baseline and the state-of-the-art algorithms in terms of both efficiency and precision. A related software is open-sourced to benefit the community.

关键词： Inverse depth parametrization Kalman filter Online calibration Visual-inertial odometry Zero velocity update

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FPGA-based Hardware Architecture For Montgomery Modular Exponentiation Algorithm*

FPGA-based Hardware Architecture For Montgomery Modular Expo...

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Intelligent Manufacturing and Industrial Big Data (ICIMIBD), International Conference on

作者： Yu Zhao Chun Zhao School of Computer Science Institution of Smart Manufacturing & Complex System BISTU Beijing Information Science and Technology University Beijing China

With the explosive growth in data communications and internet services, public key cryptography such as RSA is crucial for information privacy and security. As an important research topic, RSA can support confidentiality, authentication, data integrity and non-reputation for networks. In the process of the RSA algorithm, modular arithmetic is a fundamental operator, which requires a long time to execute, especially since the size of modular is at least 256 bits for long-term security. Montgomery Modular Multiplication (MMM) algorithm and Montgomery Modular Exponentiation (MME) algorithm are the two most popular solutions to implement modular arithmetic efficiently. But the execution time of modular arithmetic is still too long under some of the conditions. To further accelerate the modular arithmetic, this paper proposes a FPGA-based hardware architecture for MMM and MME algorithm, in which the size of the modular is 256 bits. The delay of the adder’s long carry propagation in MMM algorithm is eliminated by using carry-lookahead adder. In addition, the architexture contains a finite state machine to implement the MME algorithm and repeatedly execute the MMM algorithm. To verify the performance of the hardware architecture, the hardware design is mapped to a special device. And execution time is compared between FPGA and CPU. The result shows hardware implementation is executed 1752.5 and 628.9 times faster than the software implementation for MMM algorithm and MME algorithm respectively.

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Gm-APD LiDAR Reconstruction Algorithm with Improved Matched Filtering Based on Negative Binomial Distribution

Gm-APD LiDAR Reconstruction Algorithm with Improved Matched ...

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Academic International Symposium on Optoelectronics and Microelectronics technology (AISOMT)

作者： Hengchang Ou Jianfeng Sun Le Ma Peng Jiang National Key Laboratory of Laser Spatial Information Harbin Institute of Technology Harbin Heilongjiang China Zhengzhou Research Institute Harbin Institute of Technology Zhengzhou Henan China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China

ISBN: (数字)9798331542283

ISBN: (纸本)9798331542290

This article addresses the challenges faced by Gm-APD detectors in lidar systems when detecting weak signals. We use a triggering model based on the negative binomial distribution, which replaces the traditional Poisson distribution model, allowing for a more accurate description of the echo characteristics from rough surface targets. Building on this foundation, we have improved the conventional matched filtering algorithm by integrating the laser pulse waveform with the actual triggering response of the detector, thereby enhancing the detection rate. Experimental results demonstrate that the improved algorithm significantly increases the detection probability under low signal-to-noise ratios and with a limited number of frames, confirming the effectiveness of the new triggering model and the enhanced algorithm.

关键词： Maximum likelihood estimation Laser radar Accuracy Filtering Detectors Filtering algorithms Surface roughness Rough surfaces Photonics Signal to noise ratio

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An Interval-Peak-Based Algorithm for Range Image Reconstruction of GM-APD Lidar

An Interval-Peak-Based Algorithm for Range Image Reconstruct...

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Academic International Symposium on Optoelectronics and Microelectronics technology (AISOMT)

作者： Shihang Sun Jianfeng Sun Peng Jiang Hongchao Ni Xin Zhou Le Ma Ruobin Lin National Key Laboratory of Laser Spatial Information Harbin Institute of Technology Harbin Heilongjiang China Zhengzhou Research Institute Harbin Institute of Technology Zhengzhou Henan China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China

ISBN: (数字)9798331542283

ISBN: (纸本)9798331542290

GM-APD lidar has single-photon sensitivity, so that it can obtain 3D information of distant targets. On the other hand, the laser echo of targets is easily drowned by noise. In order to solve this problem, an interval-peak-based algorithm for range image reconstruction is proposed in this paper. Firstly, in the photon counts histogram, the x-axis is divided into small intervals and the peak value of each interval is taken. This step weakens the bad characteristic caused by the trigger probability. Secondly, according to the data feature, the trigger probability ratio coefficient and the neighborhood correlation coefficient are obtainned. Finally, the range image can be extracted by the peak method after the peak value of each interval is multiplied with this two coefficients. It is verified by the experimental data that when the SNR of target echo data is 0.022, the recovery ratio of the proposed algorithm can reach 80%, which is 25% higher than the matching filter algorithm. The proposed algorithm has a good application prospect in the range image reconstruction of GM-APD lidar.

关键词： Laser radar Three-dimensional displays Sensitivity Filtering Logic gates Approximation algorithms Spatiotemporal phenomena Image reconstruction Signal to noise ratio Photonics

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On the Approximation of the Quotient of Two Gaussian Densities for Multiple-Model Smoothing 26

On the Approximation of the Quotient of Two Gaussian Densiti...

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26th International Conference on Information Fusion, FUSION 2023

作者： Liu, Yi Li, Xi Yang, Le Mihaylova, Lyudmila Xue, Yanbo University of Canterbury Department of Electrical and Computer Engineering Christchurch New Zealand National University of Defense Technology State Key Lab of Complex Electromagnetic Environment Effects on Electronics and Information Systems Changsha China University of Sheffield Department of Automatic Control and System Engineering Sheffield United Kingdom Career Science Lab Beijing China

ISBN: (纸本)9798890344854

The quotient of two multivariate Gaussian densities can be written as an unnormalized Gaussian density, which has been applied in some recently developed multiple-model fixed-interval smoothing algorithms. However, this expression is invalid if instead of being positive definite, the covariance of the unnormalized Gaussian density is indefinite (i.e., it has both positive and negative eigenvalues) or undefined (i.e., computing it requires inverting a singular matrix). This paper considers approximating the quotient of two Gaussian densities in this case using two different approaches to mitigate the caused numerical problems. The first approach directly replaces the indefinite covariance of the unnormalized Gaussian density with a positive definite matrix nearest to it. The second approach computes the approximation through solving, using the natural gradient, an optimization problem with a Kullback-Leibler divergence-based cost function. This paper illustrates the application of the theoretical results by incorporating them into an existing smoothing method for jump Markov systems and utilizing the obtained smoothers to track a maneuvering target. © 2023 International Society of Information Fusion.

关键词： Cost functions

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Application of Automated Information system in Personnel Records Management

Application of Automated Information System in Personnel Rec...

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2024 International Conference on Decision Aid sciences and Applications, DASA 2024

作者： Dmitry, Evsykov Anatoly, Kukartsev Anna, Glinscaya Oksana, Kukartseva Yadviga, Tynchenko Bauman Moscow State Technical University Artificial Intelligence Technology Scientific and Education Center Moscow Russia Reshetnev Siberian State University of Science and Technology Department of Management Krasnoyarsk Russia Bauman Moscow State Technical University Center for Continuing Education Krasnoyarsk Russia Reshetnev Siberian State University of Science and Technology Department of System Analysis and Operations Research Krasnoyarsk Russia Siberian Federal University School of Petroleum and Natural Gas Engineering Department of Technological Machines and Equipment of Oil and Gas Complex Krasnoyarsk Russia Bauman Moscow State Technical University Artificial Intelligence Technology Scientific and Education Center Krasnoyarsk Russia

ISBN: (纸本)9798350369106

This article presents an analysis of the development of an automated information system for personnel management, with a focus on automating the hiring process. The system is designed for small and medium-sized enterprises, offering a simple and accessible solution that minimizes implementation and maintenance costs. The implementation of this system reduced documentation errors by 32 % and sped up HR data processing by 31%. Special attention is given to the technical depth of the solution: the use of MS Access for database management ensures compatibility with office tools and ease of integration. The novelty of the work lies in adapting existing automation technologies for smaller organizations with limited resources, and the creative approach is demonstrated through process optimization at minimal cost. © 2024 IEEE.

关键词： Records management

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An Improved RT-DETR-Based Object Detection Algorithm for Gm-APD LiDAR

An Improved RT-DETR-Based Object Detection Algorithm for Gm-...

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Academic International Symposium on Optoelectronics and Microelectronics technology (AISOMT)

作者： Qianxin Wang Jianfeng Sun Peng Jiang Xin Zhou Yuanxue Ding Guanlin Chen National Key Laboratory of Laser Spatial Information Harbin Institute of Technology Harbin Heilongjiang China Zhengzhou Research Institute Harbin Institute of Technology Zhengzhou Henan China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China

ISBN: (数字)9798331542283

ISBN: (纸本)9798331542290

Gm-APD LiDAR has a high sensitivity response characteristic, enabling imaging for detecting targets at extended distances, and finds broad utility. However, the highly sensitive response characteristic also makes Gm-APD LiDAR vulnerable to noise, resulting in poor imaging quality and challenging the application of target detection algorithms to this type of LiDAR. Therefore, this paper proposes a long-range vehicle detection model DRT-DETR for Gm-APD LiDAR. DRT-DETR is based on RT-DETR and employs a dual-channel feature extraction backbone, which combines with the lightweight FasterNet Block to capture semantic features from distance and intensity images effectively. It also incorporates mixed attention modules to selectively combine and enhance key features from both types of images. Attention-based Intrascale Feature Interaction employs cascaded group attention as a replacement for multi-head attention in order to minimize computational redundancy. Finally, Dysample is used instead of nearest neighbor upsampling in the cross-scale feature fusion to align features better and minimize distortion. The improved model boosts detection accuracy by 3.8% over RT-DETR and outperforms other common object detection models on the dataset, demonstrating its effectiveness.

关键词： Laser radar Sensitivity Computational modeling Vehicle detection Semantics Redundancy Imaging Object detection Feature extraction Distortion

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Radar Signal Detection Based on Ambiguity Function and Deep Learning 2

Radar Signal Detection Based on Ambiguity Function and Deep ...

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2nd International Conference on Computer Engineering and Application, ICCEA 2021

作者： Lv, Fengrong Dong, Zeyu Wan, Tao Jiang, Kaili Fang, Xueli Zhang, Lei University of Electronic Science and Technology of China School of Information and Communication Engineering Chengdu China Key Laboratory of Complex Aviation Simulation System Beijing China

ISBN: (纸本)9781665426169

The ambiguity function describes the joint characteristics of the signal in the time domain and the frequency domain, and is usually used for signal recognition. The time domain and frequency domain distribution of noise is more spurious than the signal. Its ambiguity function can also reflect its characteristics. However, the direct use of the ambiguity function as the signal feature will increase the amount of calculation of the detection system, so slice it, which reduces the burden on the system for detecting signal information while preserving the information. At the same time, the radar signal detection based on neural network can avoid the influence of artificially setting the threshold on the detection performance of the system. So, we propose an algorithm for inputting the extracted fuzzy function slice sequence into a neural network to realize signal detection. Simulation proves that when the signal-To-noise ratio of the received signal is very low, our proposed method still has a high detection probability. © 2021 IEEE.

关键词： Signal detection

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