检索结果-内蒙古大学图书馆

2021 International Conference on Big data and Intelligent Algorithms, BDIA 2021

作者： Mingyang-Luo Qiang-Lin Tongtong-Li Key Laboratory of China's Ethnic Languages and Information Technology of Ministry of Education Lanzhou730030 China School of Mathematics and Computer Science Northwest Minzu University Lanzhou730030 China Key Laboratory of Streaming Data Computing and Application Northwest Minzu University Lanzhou730124 China

Nuclear medicine SPECT is the main functional imaging modality, which plays an important role in the diagnosis and treatment of thyroid diseases. Hyperthyroidism is a common thyroid disease with symptoms such as exophthalmos, eyelid edema, and vision loss. In order to accurately segment thyroid lesions from SPECT thyroid data, a U-net-based thyroid lesion segmentation model was constructed. First, mirror, rotate, and translate the existing data. At the same time, use the generative adversarial network to expand the data. Then build a segmentation model based on U-net. Finally, perform experimental evaluation and analysis based on a set of real SPECT thyroid data. The results show that: in the traditional data expansion, the IoU value of the improved RS-U-net model is 66.83. © Published under licence by IOP Publishing Ltd.

关键词： Nuclear medicine

来源：评论

学校读者我要写书评

暂无评论

Incidence Coloring of Product Graphs of Paths

Incidence Coloring of Product Graphs of Paths

引用

2021 International Conference on Big data Analysis and Computer Science, BDACS 2021

作者： Peng, Lizhen Tian, Shuangliang Lu, Qiqi School of Mathematics and Computer Science Northwest for Minzu University Key Laboratory of Streaming Data Computing Technologies and Applications Northwest Minzu University Lanzhou China

ISBN: (纸本)9781665425612

Incidence coloring of graph refers to coloring of its all incidences in which neighborly incidences are assigned different colors. The smallest number of colors in an incidence coloring is incidence coloring number of graph. In this paper, structural coloring method and disproof method are used. we study the incidence coloring of direct products, semi-strong products and strong products of paths of different orders, and obtain the exact values of the incidence coloring numbers. The incidence coloring number of the direct product and the strong product of a path is the maximunm degree plus one. © 2021 IEEE.

关键词： Coloring

来源：评论

学校读者我要写书评

暂无评论

X-ray Classification of Tuberculosis Based on Convolutional Networks

X-ray Classification of Tuberculosis Based on Convolutional ...

引用

2021 IEEE International Conference on Artificial Intelligence and Industrial Design, AIID 2021

作者： Cao, Kai Zhang, Jingyi Huang, Mengge Deng, Tao Key Laboratory of China's Ethnic Languages and Information Technology of Ministry of Education Northwest Minzu University Gansu Lanzhou730000 China Key Laboratory of Streaming Data Computing Technologies and Application School of Mathematics and Computer Science Northwest Minzu University Gansu Lanzhou730000 China

ISBN: (纸本)9780738110837

Tuberculosis is a chronic infectious disease caused by Mycobacterium tuberculosis, which can invade many organs, and pulmonary tuberculosis is the most common infection. It is the key to treat tuberculosis to detect and diagnose the disease in the early stage. The existing computer-aided detection system has made preliminary progress in the diagnosis of pulmonary tuberculosis based on chest X-ray, but there is still a lack of further research on the classification of image signs of tuberculosis. In recent years, with the in-depth research and development in the field of deep learning, convolutional networks have emerged. Convolutional networks have achieved the best current results in image recognition, image classification, image segmentation, and other fields. Therefore, this paper applies the convolutional network to tuberculosis CT images and uses different convolutional network models to study the classification of tuberculosis CT images. Experiments show that the DenseNet121 model has higher performance than VGGNet16, VGGNet19, and ResNet152 models. As a result of classification, the accuracy rate is over 90%. © 2021 IEEE.

关键词： Image classification

来源：评论

学校读者我要写书评

暂无评论

Randomized Latent Factor Model for High-dimensional and Sparse Matrices from Industrial applications

引用

IEEE/CAA Journal of Automatica Sinica 2019年第1期6卷 131-141页

作者： Mingsheng Shang Xin Luo Zhigang Liu Jia Chen Ye Yuan MengChu Zhou the Chongqing Engineering Research Center of Big Data Application for Smart Cities and Chongqing Key Laboratory of Big Data and Intelligent ComputingChongqing Institute of Green and Intelligent TechnologyChinese Academy of Sciences the School of Computer Science and Engineering Beihang University the Department of Electrical and Computer Engineering New Jersey Institute of Technology

Latent factor(LF) models are highly effective in extracting useful knowledge from High-Dimensional and Sparse(HiDS) matrices which are commonly seen in various industrial applications. An LF model usually adopts iterative optimizers,which may consume many iterations to achieve a local optima,resulting in considerable time cost. Hence, determining how to accelerate the training process for LF models has become a significant issue. To address this, this work proposes a randomized latent factor(RLF) model. It incorporates the principle of randomized learning techniques from neural networks into the LF analysis of HiDS matrices, thereby greatly alleviating computational burden. It also extends a standard learning process for randomized neural networks in context of LF analysis to make the resulting model represent an HiDS matrix *** results on three HiDS matrices from industrial applications demonstrate that compared with state-of-the-art LF models, RLF is able to achieve significantly higher computational efficiency and comparable prediction accuracy for missing data.I provides an important alternative approach to LF analysis of HiDS matrices, which is especially desired for industrial applications demanding highly efficient models.

关键词： Big data high-dimensional and sparse matrix latent factor analysis latent factor model randomized learning

来源：评论

学校读者我要写书评

暂无评论

Clause-level Relationship-aware Math Word Problems Solver

引用

Machine Intelligence Research 2022年第5期19卷 425-438页

作者： Chang-Yang Wu Xin Lin Zhen-Ya Huang Yu Yin Jia-Yu Liu Qi Liu Gang Zhou Anhui Province Key Laboratory of Big Data Analysis and Application School of Data ScienceUniversity of Science and Technology of ChinaHefei 230026China Institute of Artificial Intelligence Hefei Comprehensive National Science CenterHefei 230088China Laboratory of Mathematical Engineering and Advanced Computing Information Engineering UniversityZhengzhou 450001China

Automatically solving math word problems,which involves comprehension,cognition,and reasoning,is a crucial issue in artificial intelligence *** math word problem solvers mainly work on word-level relationship extraction and the generation of expression solutions while lacking consideration of the clause-level *** this end,inspired by the theory of two levels of process in comprehension,we propose a novel clause-level relationship-aware math solver(CLRSolver)to mimic the process of human comprehension from lower level to higher ***,in the lower-level processes,we split problems into clauses according to their natural division and learn their *** the higher-level processes,following human′s multi-view understanding of clause-level relationships,we first apply a CNN-based module to learn the dependency relationships between clauses from word relevance in a local ***,we propose two novel relationship-aware mechanisms to learn dependency relationships from the clause semantics in a global ***,we enhance the representation of clauses based on the learned clause-level dependency *** expression generation,we develop a tree-based decoder to generate the mathematical *** conduct extensive experiments on two datasets,where the results demonstrate the superiority of our framework.

关键词： Artificial intelligence(AI) artificial neural network(ANN) computational mathematics machine intelligence machine learning

来源：评论

学校读者我要写书评

暂无评论

Structured information extraction for bone scan image report texts 4

Structured information extraction for bone scan image report...

引用

2021 4th International Conference on Advanced Algorithms and Control Engineering, ICAACE 2021

作者： Huang, Mengge Zhang, Jingyi Deng, Tao Man, Zhengxing Lin, Qiang Key Laboratory of China's Ethnic Languages and Information Technology of Ministry of Education Northwest Minzu University Lanzhou730030 China Key Laboratory of Streaming Data Computing Technologies and Application Northwest Minzu University Lanzhou730030 China School of Mathematics and Computer Science Northwest Minzu University Lanzhou730030 China

Extracting structured information from the bone scan image report text plays a crucial role in supporting clinical analysis and research. This study summarized the structure and characteristics of 3608 bone scan image report text using dictionary-based information extraction method, including data cleaning, entity recognition, building dictionary and extraction rules. This method was used to obtain the structured data of bone scan image report text required for clinical research, and the effect evaluation was carried out on 1000 randomly selected report texts, with the precision rate and recall rate higher than 90%. The method proposed in this study is practical and could have good effect on structured results for bone scan imaging report text. © Published under licence by IOP Publishing Ltd.

关键词： Clinical research

来源：评论

学校读者我要写书评

暂无评论

On Star Coloring of Several Corona Graphs 2

On Star Coloring of Several Corona Graphs

引用

2020 2nd International Conference on Electronics and Communication, Network and Computer Technology, ECNCT 2020

作者： Cai, Jin Tian, Shuangliang An, Zhuomo School of Mathematics and Computer Science Northwest for Minzu University Lanzhou730030 China Key Laboratory of Streaming Data Computing Technologies and Applications Northwest Minzu University Lanzhou730030 China

Let G be a simple graph with vertex set V(G) and edge set E(G). A vertex coloring of G is called a star coloring of G if any of the paths of 4 order are bicolored. The minimum number of colors required for a star coloring of G is denoted by ?s (G). The corona product of simple graphs G of order m and H of order n is graph G ° H with vertex set V(G ° H) = {vi |i = 1,2,?m}?{vij |i = 1,2,?m, j = 1,2,?n}, in which vi is adjacent to every vertex of Hi if and only if, vi ? V(G), vij ? V(Hi ). According to the existing graph dyeing literature, it has become a very important technical means to study the graph dyeing problem by using the graph structure operation. Therefore, it is of great significance to study the star coloring of graphs for studying the acyclic coloring and distance coloring of graphs, the study has strong application background and great theoretical value for computing graphs. In this paper, we find the upper bound of ?s (G ° H) and the exact values of ?s (G ° H) of the corona product G ° H of two graphs G and H as: ?s (G ° H) = ?s (G) + ?s (H);?s (Pm ° H) = ?s (H) + 2;?s (K 1,m ° H) = ?s (H) + 2;?s (Cn ° H) = ?s (H) + 2, where n ? 5. © 2020 Published under licence by IOP Publishing Ltd.

关键词： Graphic methods

来源：评论

学校读者我要写书评

暂无评论

Human behavior recognition based on convolutional long and short time memory network

Human behavior recognition based on convolutional long and s...

引用

2021 IEEE International Conference on Artificial Intelligence and Industrial Design, AIID 2021

作者： Zhang, Chuanlin Cao, Kai Huang, Mengge Deng, Tao School of Mathematics and Computer Science Northwest Minzu University Lanzhou China Key Laboratory of China's Ethnic Languages and Information Technology of Ministry of Education Northwest Minzu University Lanzhou China Key Laboratory of Streaming Data Computing Technologies and Application School of Mathematics and Computer Science Northwest Minzu University Lanzhou China

ISBN: (纸本)9780738110837

Convolutional long and short time memory network is a kind of fusion model, which inherits the excellent spatial feature extraction ability of convolutional neural network, and can effectively complete the processing and classification of time series data by using the memory ability of long and short time memory network to historical data and the unique gating mechanism. This paper uses the human behavior data set collected by the Wireless data Mining laboratory (WISDM) of Fordham University to predict and classify the six daily human behaviors: walking, jogging, going upstairs, going downstairs, sitting and standing. By comparing with long and short time memory network, convolutional neural network and other deep learning models, the experimental results show that the convolutional long and short time memory network has the best performance among them, which the accuracy reaches 97.43% and has a great improvement in real-time and accuracy. © 2021 IEEE.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Gradient-Based Differential kWTA Network With application to Competitive Coordination of Multiple Robots

引用

IEEE/CAA Journal of Automatica Sinica 2022年第8期9卷 1452-1463页

作者： Mei Liu Xiaoyan Zhang Mingsheng Shang Long Jin School of Information Science and Engineering Lanzhou UniversityLanzhou 730000 State Key Laboratory of Tibetan Intelligent Information Processing and Application Xining 810016China Chongqing Key Laboratory of Big Data and Intelligent Computing Chongqing Institute of Green and Intelligent TechnologyChinese Academy of SciencesChongqing 400714China Shenzhen Research Institute Lanzhou UniversityShenzhen 518063China

Aiming at the k-winners-take-all(kWTA)operation,this paper proposes a gradient-based differential kWTA(GDk WTA)*** obtaining the network,theorems and related proofs are provided to guarantee the exponential convergence and noise resistance of the proposed GD-kWTA ***,numerical simulations are conducted to substantiate the preferable performance of the proposed network as compared with the traditional ***,the GD-k WTA network,backed with a consensus filter,is utilized as a robust control scheme for modeling the competition behavior in the multi-robot coordination,thereby further demonstrating its effectiveness and feasibility.

关键词： Consensus filter k-winners-take-all(kWTA) multirobot coordination noise resistance

来源：评论

学校读者我要写书评

暂无评论

Collaborative filtering recommendation algorithm integrating user similarity and trust 4

Collaborative filtering recommendation algorithm integrating...

引用

2021 4th International Conference on Computer Information Science and application Technology, CISAT 2021

作者： Huang, Mengge Cao, Kai Zhang, Jingyi Zhang, Chuanlin Deng, Tao Key Laboratory of China's Ethnic Languages and Information Technology of Ministry of Education Northwest Minzu University Lanzhou730030 China Key Laboratory of Streaming Data Computing Technologies and Application Northwest Minzu University Lanzhou730030 China School of Mathematics and Computer Science Northwest Minzu University Lanzhou730030 China

The rapid development of the Internet has brought convenience to people and has also produced the problem of "information overload". In view of the traditional collaborative filtering algorithm facing some bottlenecks to be solved, this study proposes a collaborative filtering algorithm that combines similarity and trust. First of all, in view of the large deviation of traditional similarity calculation and prediction of user ratings, this study proposes an optimized Pearson correlation coefficient calculation method;secondly, the trust relationship is established based on the user's rating of the common project, and the trust relationship between users who do not have a direct trust relationship is established through the transfer of trust;then find the nearest neighbor set of the target user through the fusion of user similarity and trust;finally, the item is scored and predicted to generate a recommendation list. Experimental results show that the algorithm proposed in this study can effectively improve the accuracy of recommendation. © Content from this work may be used under the terms of the Creative Commons Attribution 3.0 Licence.

关键词： Collaborative filtering

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：