检索结果-内蒙古大学图书馆

2022 IEEE International Conference on High Voltage Engineering and applications, ICHVE 2022

作者： Fu, Yuwei Liang, Liejuan Zhang, Guowei Zhang, Zhiyu Chen, Chi Wang, Chuang Xi'an University of Technology Xi'an China Xi'an Xd High Voltage Apparatus Co. Ltd Xi'an710018 China

ISBN: (数字)9781665407502

ISBN: (纸本)9781665407502

With the development of sensing technology, a large number of partial discharge (PD) time domain data are generated in the field of gas-insulated integrated electrical appliances (GIS). Traditional pattern recognition methods cannot identify the defect types of such data. At the same time, deep learning methods generally face the problem of small samples. In order to solve the above problems, this paper proposes a PD pattern recognition method based on transfer learning and DenseNet model. Firstly, the finite-difference-time-domain(FDTD) method is used to simulate PD in GIS, and the time domain waveform image dataset of four PD defects was established. Secondly, image processing techniques such as image enhancement, normalization and image compression are used to process the time-domain waveform spectrum. Finally, Using CNN network and transfer learning, the recognition accuracy of the model is improved to 96.38%, and the convergence is obviously improved. The identification performance of different CNN network structures is studied, and the results show that the accuracy of DenseNet model is significantly higher than other structures. This study can be used to diagnose PD defects in GIS equipment, © 2022 IEEE.

关键词： Partial discharges

来源：评论

学校读者我要写书评

暂无评论

A New Medical image encryption Algorithm for IoMT applications 5th

A New Medical Image Encryption Algorithm for IoMT Applicati...

引用

5th Mediterranean Conference on pattern recognition and Artificial Intelligence, MedPRAI 2021

作者： Ravi, Renjith V. Goyal, S.B. Djeddi, Chawki Department of Electronics and Communication Engineering M.E.A Engineering College Kerala Malappuram India City University Petaling Jaya Malaysia Department of Mathematics and Computer Science Larbi Tebessi University Tebessa Algeria LITIS Lab Rouen University Rouen France

ISBN: (纸本)9783031041112

data security and privacy are essential for transmitting, storing, and preserving medical images. This article provides a secure chaotic framework for medical image encryption. The suggested technique has two stages: bit-level permutation and 2D SIM-based diffusion. The lossless technique is recommended for medical image encryption and decryption. It addresses the limitations of low-dimensional chaotic maps, such as small intervals and few parameters, and medical images’ unique texture and form. The keyspace of the new method is sufficiently big, and the encryption and decryption procedures are key-sensitive. Simulations and testing validate the new algorithm’s effectiveness and efficiency. According to security assessments, the algorithm is resistant to common attacks. A comparison of several encryption methods is performed. The proposed encryption method surpasses current encryption techniques when it comes to encrypting medical images. © 2022, Springer Nature Switzerland AG.

关键词： Cryptography

来源：评论

学校读者我要写书评

暂无评论

A Detailed Review on Reversible data Hiding and Its applications 1

引用

14th International Conference on Soft Computing and pattern recognition, SoCPaR 2022, and the 14th World Congress on Nature and Biologically Inspired Computing, NaBIC 2022

作者： Devineni, Venu Madhuri Pavuluri, Venkata Naga Dheeraj Manikandan, V.M. SRM University-AP Andhra Pradesh Amaravati India

ISBN: (数字)9783031275241

ISBN: (纸本)9783031275234

Reversible data concealment is a strategy that quietly alters digital material to keep secret data while allowing the original digital media to be totally restored without any error after extracting the concealed information. Reversible data hiding is often used for the content identification of visual data such as photos, films, digital records, and so forth because of its expanding demand in fields like enforcement agencies, diagnostic imaging, scientific research, and so forth. data hiding is a mechanism of securely conveying data within a multimedia container. Reversible data concealment is a way of hiding data by lightly changing digital media while permitting the original digital information to be completely restored without error if the hidden data is found. data hiding is a secure method of sending data within a multimedia container. In uses such as medical image transmission, military, and forensics, it is unlawful to destroy the original cover. data-concealing solutions are popular in these domains. After recovering the concealed data, reversible data hiding (RDH) may precisely rebuild the cover image. Without knowing the encryption key or the original content of the picture, further information can be inserted in the encrypted image. Reversible data-hiding techniques completely restore the original carrier when the secret encrypted data is removed. The classification of reversible data concealing schemes is determined by the manner of implementation. We will cover all of the ways based on Histogram Shifting, Difference Expansion, Prediction error-based approach, and compression embedding in this paper’s review. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Digital storage

来源：评论

学校读者我要写书评

暂无评论

ColorPCR: Color Point Cloud Registration with Multi-Stage Geometric-Color Fusion

ColorPCR: Color Point Cloud Registration with Multi-Stage Ge...

引用

Conference on Computer Vision and pattern recognition (CVPR)

作者： Juncheng Mu Lin Bie Shaoyi Du Yue Gao BNRist THUIBCS School of Software Tsinghua University National Key Laboratory of Human-Machine Hybrid Augmented Intelligence National Engineering Research Center for Visual Information and Applications and Institute of Artificial Intelligence and Robotics Xi'an Jiaotong University

ISBN: (数字)9798350353006

ISBN: (纸本)9798350353013

Point cloud registration is still a challenging and open problem. For example, when the overlap between two point clouds is extremely low, geo-only features may be not suf-ficient. Therefore, it is important to further explore how to utilize color data in this task. Under such circumstances, we propose ColorPCR for color point cloud registration with multi-stage geometric-color fusion. We design a Hier-archical Color Enhanced Feature Extraction module to ex-tract multi-level geometric-color features, and a GeoColor Superpoint Matching Module to encode transformation-invariant geo-color global context for robust patch corre-spondences. In this way, both geometric and color data can be used, thus leading to robust performance even under extremely challenging scenarios, such as low overlap between two point clouds. To evaluate the performance of our method, we colorize 3DMatch/3DLoMatch datasets as Color3DMatch/Color3DLoMatch and evaluations on these datasets demonstrate the effectiveness of our proposed method. Our method achieves state-of-the-art registration recall of 97.5%/88.9% on them.

关键词： Point cloud compression Computer vision Accuracy image color analysis Feature extraction pattern recognition Task analysis

来源：评论

学校读者我要写书评

暂无评论

Efficient and Confidentiality-Preserving Bloom Filter-Encoded Video Search

引用

IEEE Internet of Things Journal 2025年

作者： Yang, Xu Zhao, Hongguang Qi, Saiyu Li, Ke Wang, Qiuhao Qi, Yong Wei, Wei Mumtaz, Shahid School of Computer Science and Technology 710049 China Xi’an University of Technology School of Computer Science and Engineering Xi’an710048 China Shaanxi University of Technology School of Mathematics and Computer Science Hanzhong723000 China Silesian University of Technology Department of Applied Informatics Akademicka 16 Gliwice44-100 Poland Nottingham Trent University Department of Computer Sciences Nottingham United Kingdom

Content based video search services find extensive applications across various domains including video surveillance and object detection. In recent times, researchers have increasingly turned their attention towards enhancing the security of video search over outsourced encrypted videos. Nonetheless, prior researchers often leverage cost-expensive techniques like Homomorphic encryption or Order-preserving encryption to ensure privacy preservation. To reduce the overhead, Bloom Filter (BF)-encoded keyword search is a promising technology for retrieving encrypted videos with image queries. However, it generally suffers from serious data privacy leakage since it will reveal the inclusion relationship between "1" and "0" in the BF. Fortunately, the privacy-preserving bloom filter-based search scheme (PBKS) was recently proposed to achieve secure and effective search while protecting the values in BFs, but it still has two limitations. One is the size of a search token is very large in some cases and the other is the cloud server can infer the true value of each bit in the BF by doing a few operations. In this paper, we propose an efficient and confidentiality-preserving bloom filter-encoded video search (ECVS) scheme for retrieving encrypted videos with image queries. We first design a new CPRF (prefix-constrained pseudorandom function)-based token compression method to reduce the size of the search token and reduce the communication cost largely. Furthermore, we customize a periodic refresh mechanism to conceal the true value of each bit in the BF while avoiding excessive computational pressure on resource-limited users. Security analysis and experiments confirm the security and efficiency of our schemes. © 2014 IEEE.

关键词： Privacy by design

来源：评论

学校读者我要写书评

暂无评论

β-divergence NMF with biorthogonal regularization for data representation

引用

Engineering applications of Artificial Intelligence 2023年第1期121卷

作者： Yuan, Ruixue Leng, Chengcai Li, Bing Basu, Anup School of Mathematics Northwest University Xi'an710127 China The National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences Beijing100190 China Department of Computing Science University of Alberta EdmontonAB T6G 2E8 Canada

Non-Negative Matrix Factorization (NMF) has become a commonly used method for data representation. Orthogonal NMF improves the clustering performance by adding orthogonal constraints to the decomposed matrices. The existing orthogonal NMF methods typically use Euclidean distance to measure the difference between before and after factorization for convenience and simplicity. However, limitations of the Euclidean distance can lead to inflexibilities. In addition, failure to consider orthogonality of the decomposed features and sparsity of the data representation can also lead to degraded performance of the algorithm. In order to overcome the above shortcomings, we propose a novel β-divergence-based NMF with biorthogonal regularization (BO-βNMF). Our BO-βNMF method uses generalized β-divergence instead of Euclidean distance to measure the similarity between matrices, and selects an appropriate β for each type of data to obtain a more flexible way of measuring similarity. In addition, we also incorporate biorthogonal constraints into the minimized objective function, which ensures both orthogonality of the decomposed features and sparsity of the data representation. Furthermore, we use trace rather than Euclidean distance to measure the orthogonality of the decomposed matrices, which reduces execution time. Finally, clustering experiments on image datasets show that the overall clustering effect of BO-βNMF is better than state-of-the-art methods. © 2023 Elsevier Ltd

关键词： Matrix algebra

来源：评论

学校读者我要写书评

暂无评论

A novel low bit rate side match vector quantization algorithm based on structed state codebook

引用

MULTIMEDIA TOOLS AND applications 2019年第12期78卷 16965-16977页

作者： Wang, Yang Pan, Zhibin Li, Rui Xi An Jiao Tong Univ Sch Elect & Informat Engn Xian Shaanxi Peoples R China

Side match vector quantization (SMVQ) is a widely used image compression algorithm for data hiding applications. Compared with conventional vector quantization (VQ) algorithm, a smaller and more powerful state codebook (SC) which is generated by utilizing the correlation in natural image is used in SMVQ to achieve low bit rate. However, the visual quality of reconstructed image by using SMVQ is significantly decreased. In this paper, a novel low bit rate coding algorithm named structured SMVQ (SSMVQ) is proposed. The size of SSMVQ's SC is flexible and the SC of SSMVQ is composed by a smaller SC of conventional SMVQ and a supporting codebook which is newly introduced in this paper. Experimental results show that the proposed structed SMVQ is able to achieve satisfactory PSNR when the bit rate is extremely low.

关键词： VQ SMVQ image coding Supporting codebook Structed codebook

来源：评论

学校读者我要写书评

暂无评论

A low bit-rate SOC-based reversible data hiding algorithm by using new encoding strategies

引用

MULTIMEDIA TOOLS AND applications 2019年第15期78卷 21223-21244页

作者： Pan, Zhibin Gao, Erdun Zhu, Ruoxin Wang, Lingfei Xi An Jiao Tong Univ Sch Elect & Informat Engn Xian 710049 Shaanxi Peoples R China

Search order coding (SOC) benefits a lot from the correlation of neighboring blocks for vector quantization (VQ)-compressed images. SOC selects a number of different indices in its search path as candidate search order codes. In this work, we present a low bit-rate SOC-based reversible data hiding algorithm benefiting from novel encoding strategies which exploit the information of the placeholders. The blocks are classified into two categories by the placeholders, where different encoding strategies are designed, respectively. Firstly, for the block in smooth region, the placeholders in its neighborhood are employed to compress the VQ index. Secondly, for the block in complex region, SOC is employed to compress the VQ index. Finally, for the blocks that cannot be processed by its placeholders and SOC, an effective prediction method named accurate gradient selective prediction (AGSP) and Huffman coding are introduced. After encoding phase, the size of the output bit stream is reduced so that space is saved for data embedding. Experiment results show that our proposed method outperforms other state-of-the-art SOC-based algorithms in bit rate and embedding capacity.

关键词： Reversible data hiding image compression Search order coding (SOC) Vector quantization (VQ) Placeholder (PH) of repetition search point

来源：评论

学校读者我要写书评

暂无评论

A state codebook generation algorithm of side match vector quantization 14th

A state codebook generation algorithm of side match vector q...

引用

14th International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIH-MSP 2018

作者： Wang, Yang Pan, Zhibin Xi’an Jiaotong University Xi’an China Key Laboratory of Spectral Imaging Technology CAS Xi’an China

ISBN: (纸本)9783030037444

Side match vector quantization (SMVQ) algorithm is an effective low bit rate image compression algorithm which is very useful for data hiding techniques. By replacing the main codebook used in conventional vector quantization (VQ) with a high-quality state codebook (SC) which consists of less codewords, SMVQ algorithm can achieve both much lower bit rate than VQ and acceptable visual quality. However, the generation of the SC is of high complexity that makes the applications of SMVQ limited. To overcome this bottleneck, inequality-based fast search algorithm is used in this paper. Experimental results show that by utilizing the mean feature and the variance feature of a vector, a majority of non-closest codewords in the main codebook can be rejected and the generation of SC can be efficiently speeded up. In addition, the SC generated by using our proposed algorithm is exactly the same as the SC generated by conventional SMVQ. © Springer Nature Switzerland AG 2019.

关键词： Vector quantization

来源：评论

学校读者我要写书评

暂无评论

5th International Conference on Emerging Research in Computing, Information, Communication and applications, ERCICA 2018

5th International Conference on Emerging Research in Computi...

引用

5th International Conference on Emerging Research in Computing, Information, Communication and applications, ERCICA 2018

ISBN: (纸本)9789811359521

The proceedings contain 56 papers. The special focus in this conference is on Emerging Research in Computing, Information, Communication and applications. The topics include: IoT-Enabled Medicine Bottle;revamp Perception of Bitcoin Using Cognizant Merkle;A Novel Algorithm for DNA Sequence compression;digiPen: An Intelligent Pen Using Accelerometer for Character recognition;Design of FPGA-Based Radar and Beam Controller;effect of Lattice Topologies and Distance Measurements in Self-Organizing Map for Better Classification;evaluation and Classification of Road Accidents Using Machine Learning Techniques;Multi-language Handwritten recognition in DWT Accuracy Analysis;a Novel H-∞ Filter Based Indicator for Health Monitoring of Components in a Smart Grid;developing Ontology for Smart Irrigation of Vineyards;a Survey on Intelligent Transportation System Using Internet of Things;CRUST: A C/C++ to Rust Transpiler Using a “Nano-parser Methodology” to Avoid C/C++ Safety Issues in Legacy Code;species Environmental Niche Distribution Modeling for Panthera Tigris Tigris ‘Royal Bengal Tiger’ Using Machine Learning;organizational Digital Footprint for Traceability, Provenance Approach;bidirectional Long Short-Term Memory for Automatic English to Kannada Back-Transliteration;a Dominant Point-Based Algorithm for Finding Multiple Longest Common Subsequences in Comparative Genomics;fast and Accurate Fingerprint recognition in Principal Component Subspace;smart Meter Analysis Using Big data Techniques;movie Recommendation System;a Semiautomated Question Paper Builder Using Long Short-Term Memory Neural Networks;an Intensive Review of data Replication Algorithms for Cloud Systems;time-Critical Transmission Protocols in Wireless Sensor Networks: A Survey;impact of Shuffler Design pattern on Software Quality;privacy-Preserving Lightweight image encryption in Mobile Cloud;cyclic Scheduling Algorithm.

关键词：

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：