检索结果-内蒙古大学图书馆

IEEE International Conference on Big Data

作者： Wendan Cheng Zhen Zhang Heng Qian Qiuyue Wang Guanqun Su Lingge Meng Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center (National Supercomputer Center in Jinan) Qilu University of Technology (Shandong Academy of Sciences) Jinan China Shandong Provincial Key Laboratory of Computing Power Internet and Service Computing Shandong Fundamental Research Center for Computer Science Jinan China Shu Ju (Shandong) Intelligent Technology Co. Ltd. Jinan China Shandong Standard Institute of Emerging Technologies and Innovations Co. Ltd. Jinan China Shandong Qingniao IIoT Co. Ltd. Jinan China

ISBN: (数字)9798350362480

ISBN: (纸本)9798350362497

Industrial data collection is the foundation for implementing enterprise digitization, which is of great significance to the development of intelligent manufacturing. However, Industrial Data Collection Standards (IDCS) are primarily published in paper or PDF formats, which makes it challenging to associate and reuse knowledge. This brings difficulties to data collection and management of heterogeneous devices, thus affecting the adaptive collection of industrial data. For this reason, this paper introduces SMART into industrial data collection and proposes the construction and application of a knowledge graph-based SMART Model. First, ontology semantic reasoning and natural language processing techniques are utilized to develop an ontology model for industrial data collection and extract fine-grained IDCS knowledge. Then, the knowledge is integrated according to the standard primitive structure and conceptual reasoning rules by constructing a standard association model to form the Industrial Data Collection Standards Knowledge Graph (IDCS-KG). Finally, the SMART competence level is quantitatively assessed based on the completion degree of each operation within the SMART Model. An experimental case study demonstrates that the SMART Model can collect intelligent adaptive industrial data through the reasoning and analysis of equipment adaptation protocols and data quality management strategies.

关键词： Adaptation models Analytical models Protocols Knowledge graphs Data collection Ontologies Data models Cognition Natural language processing Standards

来源：评论

学校读者我要写书评

暂无评论

LasHeR: A large-scale high-diversity benchmark for RGBT tracking

arXiv

引用

arXiv 2021年

作者： Li, Chenglong Xue, Wanlin Jia, Yaqing Qu, Zhichen Luo, Bin Tang, Jin Sun, Dengdi Information Materials and Intelligent Sensing Laboratory of Anhui Province Anhui Provincial Key Laboratory of Multimodal Cognitive Computation School of Artificial Intelligence Anhui University Hefei230601 China Information Materials and Intelligent Sensing Laboratory of Anhui Province Key Lab of Intelligent Computing and Signal Processing of Ministry of Education Anhui Provincial Key Laboratory of Multimodal Cognitive Computation School of Computer Science and Technology Anhui University Hefei230601 China

RGBT tracking receives a surge of interest in the computer vision community, but this research field lacks a large-scale and high-diversity benchmark dataset, which is essential for both the training of deep RGBT trackers and the comprehensive evaluation of RGBT tracking methods. To this end, we present a Large-scale High-diversity benchmark for short-term RGBT tracking (LasHeR) in this work. LasHeR consists of 1224 visible and thermal infrared video pairs with more than 730K frame pairs in total. Each frame pair is spatially aligned and manually annotated with a bounding box, making the dataset well and densely annotated. LasHeR is highly diverse capturing from a broad range of object categories, camera viewpoints, scene complexities and environmental factors across seasons, weathers, day and night. We conduct a comprehensive performance evaluation of 12 RGBT tracking algorithms on the LasHeR dataset and present detailed analysis. In addition, we release the unaligned version of LasHeR to attract the research interest for alignment-free RGBT tracking, which is a more practical task in real-world applications. The datasets and evaluation protocols are available at: https://***/mmic-lcl/Datasets-and-benchmark-code. Copyright © 2021, The Authors. All rights reserved.

关键词： Large dataset

来源：评论

学校读者我要写书评

暂无评论

Threshold Image Segmentation for Non-uniform Illumination Using Otsu Optimization Approach 6th

Threshold Image Segmentation for Non-uniform Illumination Us...

引用

6th International Conference on Advanced Machine Learning Technologies and Applications, AMLTA 2021

作者： Quan, Liang Zicheng, Zhang Jinjing, Hu Chang, Kuo-Chi School of Computer Science and Mathematics Fujian University of Engineering Fuzhou China Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology No3 Xueyuan Road University Town Minhou Fuzhou Fujian350118 China School of Information Science and Engineering Fujian University of Technology No3 Xueyuan Road University Town Minhou Fuzhou Fujian350118 China

ISBN: (纸本)9783030697167

With an improved algorithm based on the Otsu method, this paper proposes solving the shadow region problem caused by non-uniform illumination. The recent image processing algorithms for handling the shaded area’s issue for the massive difference in the image grey value will not be practical. It is not easy to directly set the shaded area’s content to "black" based on this problem. This paper proposes improved threshold image segmentation for Non-uniform illumination based on the Otsu optimization Approach. It uses the local area threshold and window image pixel by sliding to enhance the image recognition rate of a shaded area. Experimental results verify that the proposed segmentation method has more robust adaptability to images with shadows. Compared with the classical global OTSU algorithm and genetic algorithm optimization, the image recognition rate is 96%. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Image recognition

来源：评论

学校读者我要写书评

暂无评论

Multi-modal Remote Sensing Image Registration via Modality Perception and Self-Supervised Position Estimation

引用

IEEE Transactions on Geoscience and Remote Sensing 2025年 63卷

作者： Xiao, Yun Zhang, Chunlei Jiang, Bo Chen, Yuan Tang, Jin Anhui University Key Laboratory of Intelligent Computing & Signal Processing (Anhui University) Anhui Provincial Key Laboratory of Security Artificial Intelligence School of Artificial Intelligence Hefei 230601 China Anhui University Information Materials and Intelligent Sensing Laboratory of Anhui Province Anhui Provincial Key Laboratory of Multimodal Cognitive Computation School of Computer Science and Technology Hefei 230601 China Anhui University School of Internet Hefei 230601 China

Multi-modal remote sensing images registration ensures that images from different sensors or modalities are spatial and informational consistent for effective comparison and analysis. However, due to the non-linear modality gaps that exist between images, making it difficult to focus only on the spatial position differences of the images and ignore the modality gaps. In this paper, to address this issue, we propose a new framework for Multi-Modal remote sensing image Registration, named MMRNet. The proposed framework comprises the following main aspects. First, a novel self-supervised Positional Misalignment Estimator (PME) is designed for multi-modal image registration. PME is able to efficiently overcome the modality gaps and learn the positional differences between multi-modal images more reliably, optimizing the registration loss by minimizing the positional differences directly. Then, a new paradigm of modality translation, termed Modality Perception Module (MPM), is introduced to effectively learn modality gaps and perform modality translation in the case of positional misalignment. Finally, we further design the modality perception guidance loss to supervise the modality translation task, which can encourage the fidelity of the generated pseudo-modality images. Our registration network integrates both rigid registration model and non-rigid registration model. Experimental results demonstrate that the proposed registration framework can obtain obviously superior performance in both rigid and non-rigid image registration tasks on optical-SAR data, optical-map data and optical-infrared data. © 1980-2012 IEEE.

关键词： image registration modality translation Multi-modal learning remote sensing processing rigid and non-rigid transformation

来源：评论

学校读者我要写书评

暂无评论

SAV-SE: Scene-aware Audio-Visual Speech Enhancement with Selective State Space Model

arXiv

引用

arXiv 2024年

作者： Qian, Xinyuan Gao, Jiaran Zhang, Yaodan Zhang, Qiquan Liu, Hexin Garcia, Leibny Paola Li, Haizhou The School of Computer and Communication Engineering University of Science and Technology Beijing Beijing100083 China The School of Electrical Engineering and Telecommunications The University of New South Wales Sydney2052 Australia The College of Computing and Data Science Nanyang Technological University Singapore The Center for Language and Speech Processing Johns Hopkins University United States The Guangdong Provincial Key Laboratory of Big Data Computing The Chinese University of Hong Kong Shenzhen518172 China Shenzhen Research Institute of Big data Shenzhen51872 China

Speech enhancement plays an essential role in various applications, and the integration of visual information has been demonstrated to bring substantial advantages. However, the majority of current research concentrates on the examination of facial and lip movements, which can be compromised or entirely inaccessible in scenarios where occlusions occur or when the camera view is distant. Whereas contextual visual cues from the surrounding environment have been overlooked: for example, when we see a dog bark, our brain has the innate ability to discern and filter out the barking noise. To this end, in this paper, we introduce a novel task, i.e. Scene-aware AudioVisual Speech Enhancement (SAV-SE). To our best knowledge, this is the first proposal to use rich contextual information from synchronized video as auxiliary cues to indicate the type of noise, which eventually improves the speech enhancement performance. Specifically, we propose the VC-S2E method, which incorporates the Conformer and Mamba modules for their complementary strengths. Extensive experiments are conducted on public MUSIC, AVSpeech and AudioSet datasets, where the results demonstrate the superiority of VC-S2E over other competitive methods. We will make the source code publicly available. Project demo page: https://***/ © 2024, CC BY.

关键词： Speech enhancement

来源：评论

学校读者我要写书评

暂无评论

Analysis of Big Data Complex Network Structure Based on Fuzzy Clustering Algorithm

Analysis of Big Data Complex Network Structure Based on Fuzz...

引用

Networking, Communications and information technology (NetCIT), International Conference on

作者： Fu Shanshan Ruan Zhiqiang Center of Modem Education Technology and Information Management Minjiang University Fujian China College of Computer and Control Engineering Minjiang University Fujian China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Fujian China Digital Fujian IoT Laboratory of Intelligent Production Fujian China

ISBN: (纸本)9781665400718

In the era of artificial intelligence with big data as the background, the statistical analysis method based on complex network has become a research hotspot and actively promoted the development of big data visualization. Complex network is a new discipline developed by cross research with other disciplines. Its network topology has obvious clustering characteristics, that is, complex network cluster structure. Together with small world and scale-free, it is called the three most important and basic attributes of complex network topology. The fundamental purpose of complex network clustering algorithm is to detect the actual network cluster structure in complex network, which has very important practical value for mining the cluster structure in network and understanding its characteristics, and is conducive to understanding the functions of network, such as predicting the development of complex network, analyzing the behavior of social network, discovering hot topics on network, etc. This paper combines the methods and ideas of complex network analysis, carries out the method design and research of organization analysis, and tries to solve the relationship and characteristics of inter departmental cooperation within the organization.

关键词： Visualization Data analysis Heuristic algorithms Data visualization Clustering algorithms Complex networks Organizations

来源：评论

学校读者我要写书评

暂无评论

Orthogonal Dual Graph Regularized Nonnegative Matrix Factorization 11th

Orthogonal Dual Graph Regularized Nonnegative Matrix Factori...

引用

11th International Conference on Image and Graphics, ICIG 2021

作者： He, Jinrong Shi, Yanxin Bai, Zongwen Bao, Zeyu Key Laboratory of Agricultural Internet of Things Ministry of Agriculture and Rural Affairs Northwest A&F University Shaanxi Yangling712100 China College of Mathematics and Computer Science Yan‘an University Yan‘an716000 China Shaanxi Key Laboratory of Agricultural Information Perception and Intelligent Service Northwest A&F University Shaanxi Yangling712100 China Shaanxi Key Laboratory of Intelligent Processing for Big Energy Data Yanan University Shaanxi Yan’an716000 China University of Science and Technology of China Anhui Hefei230026 China

ISBN: (纸本)9783030873578

Nonnegative matrix factorization (NMF) is a classical low-rank approximation method of data matrix, which decomposes a high-dimensional data matrix into two nonnegative low-rank matrices, namely basis matrix and coefficient matrix. In order to capture the local geometric structure of original dataset, manifold learning methods are incorporated into NMF framework. Motivated by recent progress in dual graph regularization, by considering the geometric structures of both the data manifold and the feature manifold, Orthogonal Dual-graph NMF (ODNMF) algorithms were proposed, which imposed orthogonality constraints on basis matrix or coefficient matrix. Since the projection directions were mutually orthogonal, the representation power of data samples was enhanced, thus ODNMF methods are more robust for data clustering. The extensive experimental results on UCI, text and face image data sets have demonstrated the superiority of the proposed methods. © 2021, Springer Nature Switzerland AG.

关键词： Matrix algebra

来源：评论

学校读者我要写书评

暂无评论

Research on Differential Power Analysis of Lightweight Block Cipher LED

Research on Differential Power Analysis of Lightweight Block...

引用

作者： Yi Zou Lang Li Hui-huang Zhao Ge Jiao College of Computer Science and Technology Hengyang Normal University Human Provincial Key Laboratory of Intelligent Information Processing and Application

LED algorithm is a new lightweight encryption algorithm proposed in CHES 2011, which is used for IOT to protect the communication security of RFID tags and smart cards. It has been found that it is possible to retrieve secret key of algorithm by appropriate analysis of the devices' s power consumption,and the differential power analysis is the most powerful attack. This paper proposed a method of differential power analysis on LED algorithm. Combined with hardware circuit, it designed and implemented differential power analysis of the LED encryption system. The experimental results show that method which is proposed in this paper was cracked the 64 bits key of LED. Thus,without protection, the cipher LED would be difficult to resist differential power analysis. and according this, We provide a general analysis method of differential power analysis on other lightweight cryptographic algorithms.

关键词： Lightweight block cipher Differential power analysis LED

来源：评论

学校读者我要写书评

暂无评论

WeChat Public Platform for Customers Reserving Bank Branches Based IoT

WeChat Public Platform for Customers Reserving Bank Branches...

引用

作者： Jie Chen Xiaoman Liang Jian Zhang College of Computer Science and Technology Hengyang Normal University Hunan Provincial Key Laboratory of Intelligent Information Processing and Application

With the developing of the social economy,the amount of currency circulation has increased and become more frequent,but the customer gathering is often occurred in the many bank's *** this paper,with some framework technology,Spring Boot and MyBatis,a WeChat public platform software is developed for customers who are available to book branch business,such as branch service reservation,bank business reservation,reservation information inquiry and so *** with WeChat public number and small program,the software offers humanized service and simple ***,it can meet the needs of users who can choose a reasonable time to go to the ideal branch to handle their business quickly,which not only saves users' time,but also improves the efficiency of the bank's system.

关键词： Reservation Branch WeChat public platform

来源：评论

学校读者我要写书评

暂无评论

The Optimal Implementation of Khudra Lightweight Block Cipher

The Optimal Implementation of Khudra Lightweight Block Ciphe...

引用

作者： Xiantong Huang Lang Li Ying Guo College of Computer Science and Technology Hengyang Normal University Hunan Provincial Key Laboratory of Intelligent Information Processing and Application

In this paper,we discuss the area and speed balance optimization of Khudra lightweight block *** are three major ***,because the whole structure of the Khudra block cipher and its F-function are based on a Feistel structure,we make the main module directly call the Ffunction in the hardware optimization ***,through the clock control,the plaintext can be XORed with the key and the round constant under certain *** the same time,the 3 rounds of the F-function are merged into one module,whose F-function module contains the F-function of the left and right branches of the ***,three rounds of operations can be completed with only one S-box,which can effectively reduce the number of registers and the number of iterations to increase the encryption and decryption ***,because of the particularity of key expansion in Khudra,we separately calculated the round key and stored its results in the register,which can effectively save the time of key expansion.

关键词： Lightweight block cipher Khudra Optimization FPGA implementation

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：