检索结果-内蒙古大学图书馆

Conference on Applied Optics and Photonics (AOPC) - Image Processing and Analysis

作者： Chen, Zhibin Qin, Mengze Song, Yan Xiao, Wenjian Ordnance Engn Coll Inst Ordnance Technol Shijiazhuang 050000 Peoples R China

ISBN: (纸本)9781628419009

Multi-spectral integration target consists of collimator, lighting and target plate with cross-line and four-bar target. The high brightness image of four-bar target and stray light have a serious impact on the auto extraction for center of cross-line when do the optical axis parallelism on-line test using the multi-spectral target. To solve the problem, a fast and accurate extraction algorithm for center of cross-line based on two windows scanning was proposed. Firstly, using thresholding techniques get rid of the low brightness stray light. Then, using two windows scanning method get rid of the image of high brightness four-bar target and get the cross-line area. Lastly, according to the results to find the corresponding area in the gray-scale map of the original image, using energy accumulation method find the extreme point of energy. The value of x-axis and y-axis is the position of the center of cross-line. The results show that the algorithm is fast and accurate and can realize the extraction for center of cross-line under the influence of the high brightness four-bar target and stray light.

关键词： Multi-spectral optical axis parallelism Two windows scanning extraction algorithm

来源：评论

学校读者我要写书评

暂无评论

The Joint extraction algorithm Based on Color and Depth Information

The Joint Extraction Algorithm Based on Color and Depth Info...

引用

2015 Joint International Mechanical,Electronic and Information Technology Conference(JIMET 2015)

作者： Zijuan Zhang Shaanxi Polytechnic Institute

ISBN: (纸本)9781510817982

For importance map, most image retargeting algorithms use color information only(such as the gradient map or saliency map, etc.) to deal with this problem. This paper considers depth information based on the analysis of the depth map besides, combines with color information and puts forward a combined color depth information's importance map. The importance map can accurately identify the subject of source information. Guided by this importance map, retargeting results can protect the important areas in the source image better and obtain the better effects.

关键词： Depth Map Importance Map extraction algorithm Image Retargeting

来源：评论

学校读者我要写书评

暂无评论

Deep Learning Based algorithm for Efficient Information Retrieval in Blockchain Transactions 6

Deep Learning Based Algorithm for Efficient Information Retr...

引用

6th IEEE Symposium on Computers and Informatics, ISCI 2024

作者： Subrmanian, Kayalvizhi Thangarasu, Gunasekar Yanyan, Zhao Kannan, K Nattar Faculty of Engineering and It Deptartment of Applied Science Saveetha School of Engineering India Mahsa University Universiti Teknologi Petronas Malaysia Saveetha Institute of Medical and Technical Sciences Chennai India Department of Digital Health and Health Informatics Saveetha School of Engineering India Imu Univeristy Saveetha Institute of Medical and Technical Sciences Chennai India Spt Energy Group Department of Finance Beijing China Saveetha Institute of Medical and Technical Sciences Saveetha School of Engineering Chennai India

ISBN: (纸本)9798350353853

DeepBlock is a state-of-the-art extraction algorithm leveraging advanced deep learning to facilitate efficient information retrieval from blockchain transactions. With the rapid expansion of blockchain technology, the ability to analyze and extract meaningful data from the enormous volume of transaction records has become increasingly vital. DeepBlock addresses this need by employing sophisticated deep learning techniques to autonomously identify and extract pertinent information from blockchain transactions. This innovative approach enables users to seamlessly access, and process valuable data stored within the blockchain, significantly improving efficiency and accuracy in data retrieval tasks. DeepBlock's cutting-edge algorithm not only enhances the extraction process but also adapts to the dynamic and complex nature of blockchain data, ensuring high relevance and precision. By streamlining information retrieval, DeepBlock empowers users to leverage blockchain technology more effectively, unlocking new possibilities for data analysis and application in various fields. Whether for financial analysis, regulatory compliance, or research, DeepBlock's deep learning-based extraction capabilities represent a significant advancement in harnessing the full potential of blockchain data. © 2024 IEEE.

关键词： Deep learning DeepBlock extraction algorithm Information retrieval

来源：评论

学校读者我要写书评

暂无评论

Hybrid image steganography method using Lempel Ziv Welch and genetic algorithms for hiding confidential data

引用

MULTIDIMENSIONAL SYSTEMS AND SIGNAL PROCESSING 2022年第2期33卷 561-578页

作者： Almawgani, A. H. M. Alhawari, Adam R. H. Hindi, Ayman Taher Al-Arashi, Waled Hussein Al-Ashwal, A. Y. Najran Univ Coll Engn Elect Engn Dept Najran Saudi Arabia Univ Sci & Technol Fac Engn Dept Elect Engn Sanaa Yemen

Digital images are commonly used in steganography due to the popularity of digital image transfer and exchange through the Internet. However, the tradeoff between managing high capacity of secret data and ensuring high security and quality of stego image is a major challenge. In this paper, a hybrid steganography method based on Haar Discrete Wavelet Transform, Lempel Ziv Welch algorithm, Genetic algorithm, and the Optimal Pixel Adjustment Process is proposed to improve the quality of the stego image and increase the capacity for secret data. The cover image is divided into non-overlapping blocks of n x n pixels. Then, the Haar Discrete Wavelet Transform is used to increase the robustness of the stego image against attacks. In order to increase the capacity for, and security of, the hidden image, the Lempel Ziv Welch algorithm is applied on the secret message. After that, the Genetic algorithm is employed to give the encoded and compressed secret message cover image coefficients. The Genetic algorithm is used to find the optimal mapping function for each block in the image. Lastly, the Optimal Pixel Adjustment Process is applied to reduce the error, i.e., the difference between the cover image blocks and the stego image blocks. This step is a further improvement to the stego image quality. The proposed method was evaluated using four standard images as covers and three types of secret messages. The results demonstrate higher visual quality of the stego image with a large size of embedded secret data than what is generated by already-known techniques. The experimental results show that the information-hiding capacity of the proposed method reached to 50% with high PSNR (52.83 dB). Thus, the herein proposed hybrid image steganography method improves the quality of the stego image over those of the state-of-the-art methods.

关键词： Discrete wavelet aransform Embedding algorithm extraction algorithm Genetic algorithm Lempel Ziv Welch (LZW) algorithm Steganography

来源：评论

学校读者我要写书评

暂无评论

extraction algorithm of complicated avionics fault diagnosis rules based on rough sets

Extraction algorithm of complicated avionics fault diagnosis...

引用

第五届国际自动化测试与仪器仪表学术会议

作者： Zhao Xin Cheng Jinjun Huang Hanqiao Yuan Huanhuan ATS Lab. Air Force Engineering University the 660thResearch Institute of AVIC

With the problem of lacking fault samples of complicated avionics,in order to simplify test process and improve diagnosis efficiency,a method for extracting diagnosis rules based on rough set was promoted.A fault diagnosis decision-making information system was constructed to calculate all reductions of test-parameter-set by building decision-making distinguishing matrix and decision-making distinguishing functions of the fault diagnosis information system,so that the fault diagnosis rules can be *** example,the method for extracting diagnosis rules was used in the diagnosis of some RF system,with the result that 9 test parameters used for diagnosis were reduced to *** result of the study shows that the method can efficiently reduce the test-parameter-set and extract fault diagnosis rules under the condition of small *** it is helpful for simplifying test process and improving the diagnosis ability.

关键词： Rough Set Small-sample Avionics Fault Diagnosis extraction algorithm

来源：评论

学校读者我要写书评

暂无评论

Design of college student employment service platform based on cloud computing

Design of college student employment service platform based ...

引用

Euro-Asia Conference on Frontiers of Computer Science and Information Technology (FCSIT)

作者： Zhang, Yuchen Li, Xin Sun, Tianjian Zhang, Yu Cheng, Yuhang Li, Jiaqi Tiangong Univ Sch Econ & Management Tianjin Peoples R China Tiangong Univ Coll Comp Sci & Technol Tianjin Peoples R China Tiangong Univ Sch Elect & Informat Engn Tianjin Peoples R China

ISBN: (纸本)9781665463539

Traditional recruitment methods are no longer suitable for the current situation. With the rapid development of online recruitment, the employment situation of college students is becoming more and more severe. Based on this situation, this paper studies data crawler, visualization and analysis technology, and designs a cloud-based employment service platform for college students to help them understand the recruitment information and current situation. This project is written by python Web application framework Django, the purpose is to research the establishment of a convenient college students in the shortest time to find a suitable job platform;The main content includes five functional modules: data crawler and processing, data visualization, cloud computing and job recommendation. The design structure of this platform makes the recruitment data more clear and intuitive for job seekers, universities and enterprises, and has guiding significance for the job hunting and employment of contemporary college students.

关键词： Cloud computing Employment service platform extraction algorithm

来源：评论

学校读者我要写书评

暂无评论

Feature extraction for Medical CT Images of Sports Tear Injury

引用

MOBILE NETWORKS & APPLICATIONS 2021年第1期26卷 404-414页

作者： Nie, Qi Zou, Ye-bing Lin, Jerry Chun-Wei Jiangxi Univ Tradit Chinese Med Phys Educ Dept Nanchan 330004 Peoples R China Western Norway Univ Appl Sci Dept Comp Sci Elect Engn & Math Sci N-5063 Bergen Norway

Analysis of medical CT images directly affects the accuracy of clinical case diagnosis. Therefore, feature extraction problem of medical CT images is extremely important. A feature extraction algorithm for medical CT images of sports tear injury is proposed. First, CT images are decomposed into a low frequency component and a series of high frequency components in different directions by wavelet fast decomposition method. The high- and low-frequency information of CT images is enhanced by wavelet layered multi-directional image enhancement algorithm, and the multi-scale enhancement for medical CT images of sports tear injury is completed. Then, edge of the enhanced CT images is extracted using an image edge extraction algorithm based on extended mathematical morphology. Finally, based on the extracted edge information of CT images, feature extraction for medical CT images of sports tear injury is completed by the NSCT-GLCM based CT image feature extraction algorithm. Research results show that the proposed algorithm effectively extracts CT image features of sports tear injury and provides auxiliary information for doctor diagnosis.

关键词： Sports tear injury Medical CT Image feature extraction algorithm Fast wavelet transform Multi-scale enhancement

来源：评论

学校读者我要写书评

暂无评论

A Theoretical Nonlinear Regression Model of Rainfall Surface Flow Accumulation and Basin Features in Park-Scale Urban Green Spaces Based on LiDAR Data

引用

WATER 2023年第13期15卷 2442页

作者： Huang, Hengshuo Tian, Yuan Wei, Mengjia Jia, Xiaoli Wang, Peng Ackerman, Aidan C. Chatterjee, Siddharth G. Liu, Yang Tian, Guohang SUNY Coll Environm Sci & Forestry 1 Forestry Dr Syracuse NY 13210 USA Univ Alaska Fairbanks Geophys Inst 2156 Koyukuk Dr Fairbanks AK 99775 USA Henan Agr Univ Coll Landscape Architecture & Art 63 Nongye Rd Zhengzhou 450002 Peoples R China Hungarian Univ Agr & Life Sci MATE Inst Landscape Architecture Urban Planning & Garde Varmegye U 3-5 H-1052 Budapest Hungary Management Ctr Zhengzhou Green Expo Pk Renwen Rd Zhengzhou 451464 Peoples R China

Green infrastructure is imperative for efficiently mitigating flood disasters in urban areas. However, inadequate green space planning under rapid urbanization is a critical issue faced by most Chinese cities. Aimed at theoretically understanding the rainwater storage capacity and improvement potential of urban green spaces, a synthetic simulation model was developed to quantify rainfall surface flow accumulation (FA) based on the morphological factors of a flow basin: the area, circumference, maximum basin length, and stream length sum. This model consisted of applying the Urban Forest Effects-Hydrology model (UFORE-Hydro) to simulate the actual precipitation-to-surface runoff ratio through a procedure involving canopy interception, soil infiltration, and evaporation;additionally, a relatively accurate multiple flow direction-maximum downslope (MFD-md) algorithm was applied to distribute the surface flow in a highly realistic manner, and a self-built "extraction algorithm" extracted the surface runoff corresponding to each studied basin alongside four fundamental morphological parameters. The various nonlinear regression functions were assessed from both univariable and multivariable perspectives. We determined that the Gompertz function was optimal for predicting the theoretical quantification of surface FA according to the morphological features of any given basin. This article provides parametric vertical design guidance for improving the rainwater storage capacities of urban green spaces.

关键词： surface runoff k-means cluster hydrological model theoretical simulation extraction algorithm MFD-md

来源：评论

学校读者我要写书评

暂无评论

A Novel Method of Forecasting Chaotic and Random Wind Speed Regimes Based on Machine Learning with the Evolution and Prediction of Volterra Kernels

引用

ENERGIES 2023年第12期16卷 4766页

作者： Abdul Majid, Amir Univ Sci & Technol Fujairah Coll Engn & Technol Elect Engn Dept POB 2202 Fujairah U Arab Emirates

This study aims to focus on using the Volterra series and machine learning for forecasting random and chaotic wind speed regimes, since calm weather is mostly noticed at the local site, making dataset selection difficult. A novel method is proposed to predict Volterra kernels up to the third order, using a forward-back propagation neural network with 12-month measurements at Fujairah site (United Arab Emirates). Both daily and monthly wind speed datasets are investigated for forecasting. The three dominant hourly and daily kernels are extracted for each day and each month. Predicted future Volterra kernels are estimated from past values using both statistical analysis and individual neuro networks for each of the Volterra kernel coefficients. Using the evolved Volterra kernels, the hourly and daily wind speeds are forecasted with similar patterns of the measured values. Due to the random nature of wind speed at the local site, a two-layer with four neurons per layer neuro network is used to locate the most variable and intense speed during 8 h in the day. Forecasted wind speed is determined with errors arising from different sources, such as the utilization of only third-order Volterra kernels and the difficulty of machine training of the employed shallow network. Nevertheless, this work depicts a useful algorithm to forecast chaotic and random wind speed regimes. Computational time is a trade of the complexity of Volterra mathematical analysis.

关键词： error estimation Korhonen network machine learning extraction algorithm Volterra kernels wind speed prediction

来源：评论

学校读者我要写书评

暂无评论

A Sensitive Data extraction algorithm Based on the Content Associated Encryption Technology for ICS

A Sensitive Data Extraction Algorithm Based on the Content A...

引用

International Workshop on Information Storage / 9th International Symposium on Optical Storage

作者： Wang Wei Huang Hao Xie Changsheng Huazhong Univ Sci & Technol Sch Comp Sci & Technol Wuhan Natl Lab Optoelect Wuhan 430074 Peoples R China

ISBN: (纸本)9780819495853

With the development of HD video, the protection of copyright becomes more complicated. More advanced copyright protection technology is needed. Traditional digital copyright protection technology generally uses direct or selective encryption algorithm and the key does not associate with the video content [1]. Once the encryption method is cracked or the key is stolen, the copyright of the video will be violated. To address this issue, this paper proposes a Sensitive Data extraction algorithm (SDEA) based on the content associated encryption technology which applies to the Internet Certification Service (ICS). The principle of content associated encryption is to extract some data from the video and use this extracted data as the key to encrypt the rest data. The extracted part from video is called sensitive data, and the rest part is called the main data. After extraction, the main data will not be played or poorly played. The encrypted sensitive data reach the terminal device through the safety certificated network and the main data are through ICS disc. The terminal equipments are responsible for synthesizing and playing these two parts of data. Consequently, even if the main data on disc is illegally obtained, the video cannot be played normally due to the lack of necessary sensitive data. It is proved by experiments that ICS using SDEA can destruct the video effectively with 0.25% extraction rates and the destructed video cannot be played well. It can also guarantee the consistency of the destructive effect on different videos with different contents. The sensitive data can be transported smoothly under the home Internet bandwidth.

关键词： content associated sensitive data extraction algorithm Logistic Chaotic Mapping encryption

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：