检索结果-内蒙古大学图书馆

Journal of Digital Information Management 2007年第3期5卷 99-106页

作者： Xu, Zhihong Zheng, Xin Guo, Ping Image Processing and Pattern Recognition Laboratory Beijing Normal University Beijing 100875 China School of Computer Science Beijing Institute of Technology Beijing 100081 China

The software systems which are related to national science and technology projects are very crucial. This kind of systems always involves high technical factors and has to spend a large amount of money, so the quality and reliability of the software deserve to be further studied. Hence, we propose to apply four intelligent classification techniques most used in data mining fields, including Bayesian belief networks (BBN), nearest neighbor (NN), rough set (RS) and decision tree (DT), to validate the usefulness of software metrics for risk prediction. Results show that comparing with metrics such as Lines of code (LOC) and Cyclomatic complexity (V(G)) which are traditionally used for risk prediction, Halstead program difficulty (D), Number of executable statements (EXEC) and Halstead program volume (V) are the more effective metrics as risk predictors. By analyzing obtained results we also found that BBN was more effective than the other three methods in risk prediction.

关键词： Bayesian networks

来源：评论

学校读者我要写书评

暂无评论

Mallat fusion for multi-source remote sensing classification

Mallat fusion for multi-source remote sensing classification

引用

ISDA 2006: Sixth International Conference on Intelligent Systems Design and Applications

作者： Dongdong, Cao Qian, Yin Ping, Guo IEEE Image Processing and Pattern Recognition Laboratory Beijing Normal University Beijing 100875 China

ISBN: (纸本)0769525288

The fusion of multi-source remote sensing data is to offer improved accuracies in land cover classification. The conventional fusion methods such as HIS and PCA can not enhance information and simultaneously preserve high fidelity. Thus, the fused image is not preferable for classification. In this paper, the multi-source remote sensing data fusion based on Mallat algorithm for classification is proposed. The purpose of fusion is to create a new image that is more suitable for recognition. The topic focuses on the pyramid decomposition and choosing coefficients in the fusion process. The performance of proposed method is assessed by statistical methods and its effectiveness also testified by classification accuracies. © 2006 IEEE.

关键词： Remote sensing

来源：评论

学校读者我要写书评

暂无评论

PupilFace: A Cascaded Face Detection and Location Network Fusing Attention 18th

PupilFace: A Cascaded Face Detection and Location Network Fu...

引用

18th Pacific Rim International Conference on Artificial Intelligence, PRICAI 2021

作者： Li, Xiang Zou, Jiancheng Image Processing and Pattern Recognition Laboratory North China University of Technology Beijing100000 China

ISBN: (纸本)9783030893699

Although the development of uncontrolled face detection and location technology have made great progress, there are some problems needing to be solved in more complicated situation, such as massive occlusion and pose variation. In this paper, we propose a robust one-stage face detection and location network named PupilFace. It can locate faces of different sizes at the pixel level in complex scenarios. Specifically, we have made contributions in the following three aspects: (1) Using a lightweight backbone, we can not only detect images of dense faces, but also mark facial landmarks in pictures of various scale. In this paper, the pictures are difficult to detect because of massive occlusion or tiny faces. On the WIDER FACE hard test set, PupilFace performs better than other state-of-the-art networks. (2) The addition of the attention module–Hard Efficient Channel Attention (HECA), proposed by us, enhances the connection between the feature channels and improves the detection performance without reducing the dimension. The parameters and computations of HECA, against the parameters and computations of MobileNetV2 are 9 vs. 3.34M and 5.1e−4 GFLOPs vs. 0.32 GFLOPs. (3) We can employ varying-depths backbones accordingly to different detection and location tasks, so the model can be popularized in different fields. Extra annotations and code have been made available at: https://***/Ideal-maths/PupilFace. © 2021, Springer Nature Switzerland AG.

关键词： Face recognition

来源：评论

学校读者我要写书评

暂无评论

Cost reference particle filter based on adaptive particle swarm optimization in observation uncertainty

Cost reference particle filter based on adaptive particle sw...

引用

作者： Hu, Zhen-Tao Liu, Xian-Xing Jin, Yong Laboratory of Image Processing and Pattern Recognition Henan University Kaifeng 475001 China

ISBN: (纸本)9789881725592

Aiming at the effective approximation of sampling particle set relative to system state in observation uncertainty, a novel cost reference particle filter based on adaptive particle swarm optimization is proposed. In the new algorithm, the cost function and the risk function are firstly introduced to realize reasonable utilization of the latest observation. In addition, according to the prior modeling information, a new adaptive method is given to solve the selection of limit velocity. And then the movement of particle set towards the region of high weight particle is completed by particle swarm optimization strategy. The algorithm realizes the dynamic combination of the cost reference particle filter and the adaptive particle swarm optimization, and the reliability and stabilize of sampling particle set relative to system state are improved. The theoretical analysis and experimental results show the efficiency of the proposed algorithm. © 2011 Chinese Assoc of Automati.

关键词： Costs

来源：评论

学校读者我要写书评

暂无评论

Research on a novel restoration algorithm of turbulence-degraded images with alternant iterations

引用

Journal of Systems Engineering and Electronics 2006年第3期17卷 477-482页

作者： Liu Chunsheng Hong Hanyu Zhang Tianxu Inst. for Pattern Recognition and AI State Key Laboratory of Image Processing and Intelligent Control Huazhong Univ. of Science and Technology Wuhan 430074 P. R. China

A new restoration algorithm based on double loops and alternant iterations is proposed to restore the object image effectively from a few frames of turbulence-degraded images, Based on the double loops, the iterative relations for estimating the turbulent point spread function PSF and object image alternately are derived. The restoration experiments have been made on computers, showing that the proposed algorithm can obtain the optimal estimations of the object and the point spread function, with the feasibility and practicality of the proposed algorithm being convincing.

关键词： turbulence-degraded image image restoration double loops alternant iterations.

来源：评论

学校读者我要写书评

暂无评论

Maintaining imbalance highly dependent medical data using dirichlet process data generation

Maintaining imbalance highly dependent medical data using di...

引用

2011 6th International Conference on Digital Information Management, ICDIM 2011

作者： Antaresti, Tieta Fanany, Mohamad Ivan Arymurthy, Aniati Murni Pattern Recognition Image Processing and Content-Based Image Retrieval Laboratory Faculty of ComputerScience Universitas Indonesia Depok 16424 Indonesia

ISBN: (纸本)9781457715389

The existence of imbalanced data between one class and another class is an important issue to be considered in a classification problem. One of the well-known data balancing technique is the artificial oversampling, which increase the size of datasets. In this research, multinomial classification was applied to classify some recorded features obtained from a single ECG (electrocardiograph) sensor. Therefore, a Dirichlet process, a dirichlet distribution of cumulative distribution function of each data partition, was needed to model the distribution of the new generated data by also considering the statistical properties of the previous data. Data balancing process had given the result of 77.21% classification accuracy (CA), and 90.9% area under ROC curve (AUC). © 2011 IEEE.

关键词： Distribution functions

来源：评论

学校读者我要写书评

暂无评论

Applications of artificial intelligence to lipid nanoparticle delivery

引用

Particuology 2024年第7期90卷 88-97页

作者： Ye Yuan Yuqi Wu Jiabei Cheng Kaiyuan Yang Yilin Xia Hongguang Wu Xiaoyong Pan Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong UniversityKey Laboratory of System Control and Information ProcessingMinistry of Education of ChinaChina Songjiang Research Institute Songjiang District Central HospitalShanghai Jiao Tong University School of MedicineShanghaiChina

Lipid nanoparticles(LNPs)are nanocarriers composed of four lipid components and can be used for gene therapy,protein replacement,and vaccine ***,LNPs also face several challenges,such as toxicity,immune activation,and low delivery *** overcome these challenges,artificial intelligence can be used to optimize the design and formulation of LNPs,as well as to predict their properties and ***,antibody-targeted conjugation can be used to enhance the specificity and selectivity of LNPs by attaching an antibody that recognizes a specific antigen on the cell surface to LNPs.

关键词： Artificial intelligence Lipid nanoparticles Antibody Targeted conjugation

来源：评论

学校读者我要写书评

暂无评论

GFENet: Enabling Attention and Adaptive Feature Fusion in Real-time Object Detection 2

GFENet: Enabling Attention and Adaptive Feature Fusion in Re...

引用

2nd International Symposium on Electrical, Electronics and Information Engineering, ISEEIE 2022

作者： Pan, Chaolin Zhu, Xiaoyang Chu, Jun Nanchang Hangkong University Department of Key Laboratory of Jiangxi Province for Image Processing and Pattern Recognition Nanchang China

ISBN: (数字)9781665468749

ISBN: (纸本)9781665468749

Real-time object detection has been a critical component of onboard instrumentation for next-generation autonomous driving. To enable safety and reliability in autonomous driving systems, we must continue advancing its real-time object detection accuracy for future autonomous driving systems in complex environments. Existing works in real-time object detection cannot accurately detect objects with similar appearances and in complex environments. In particular, existing approaches missed many essential features because of the loss of multi-scale contextual features. Therefore, they cannot differentiate objects that have a similar appearance, a low-resolution, and a small size. To solve these issues, and to advance real-time object detection accuracy, we develop GFENet (Global Feature Enhancement Network), an end-to-end real-time object detection framework. First, we introduce a convolutional attention module that integrates spatial and channel-wise features and eliminates ineffective features to enable a strong feature representation of the network, followed by a lightweight residual module that further advances the feature representation by highlighting salient changes in features. Second, we build an adaptive feature fusion module to adaptively learn weights of multi-scale contextual features across layers, aiming to strengthen weights for small-size objects. We comprehensively evaluate GFENet on two leading object detection datasets-PASCAL VOC and MS COCO. The evaluation results (mAP of 82.9 and FPS of 31 on PASCAL VOC;mAP of 39.0 and FPS of 23 on MS COCO) show the outperformance of GFENet compared to competing baseline methods. © 2022 IEEE.

关键词： Instruments Object detection Detectors Feature extraction Real-time systems Safety Reliability

来源：评论

学校读者我要写书评

暂无评论

An image compression-encryption algorithm based on 2-D compressive sensing

引用

Journal of Computational Information Systems 2013年第24期9卷 10057-10064页

作者： Mo, Yan Zhang, Aidi Zheng, Fen Zhou, Nanrun Jiangxi Province Key Laboratory of Image Processing and Pattern Recognition Nanchang Hangkong University Nanchang 330063 China Department of Electronic Information Engineering Nanchang University Nanchang 330031 China

An image compression-encryption algorithm based on 2-D compressive sensing is proposed, which can accomplish encryption and compression simultaneously. The measurements are performed in two directi-ons and the measurement matrices are constructed as partial Hadamard matrices, which are controlled by chaos map. The proposed algorithm is sensitive to the keys and it can resist various attacks. Simulation results verify the validity and reliability of the proposed algorithm. Copyright © 2013 Binary Information Press.

关键词： Compressed sensing

来源：评论

学校读者我要写书评

暂无评论

Mem Brain: An Easy-to-Use Online Webserver for Transmembrane Protein Structure Prediction

引用

Nano-Micro Letters 2018年第1期10卷 12-19页

作者： Xi Yin Jing Yang Feng Xiao Yang Yang Hong-Bin Shen Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Department of Computer Science Shanghai Jiao Tong University Key Laboratory of Shanghai Education Commission for Intelligent Interaction and Cognitive Engineering

Membrane proteins are an important kind of proteins embedded in the membranes of cells and play crucial roles in living organisms, such as ion channels,transporters, receptors. Because it is difficult to determinate the membrane protein's structure by wet-lab experiments,accurate and fast amino acid sequence-based computational methods are highly desired. In this paper, we report an online prediction tool called Mem Brain, whose input is the amino acid sequence. Mem Brain consists of specialized modules for predicting transmembrane helices, residue–residue contacts and relative accessible surface area of a-helical membrane proteins. Mem Brain achieves aprediction accuracy of 97.9% of ATMH, 87.1% of AP,3.2 ± 3.0 of N-score, 3.1 ± 2.8 of C-score. Mem BrainContact obtains 62%/64.1% prediction accuracy on training and independent dataset on top L/5 contact prediction,respectively. And Mem Brain-Rasa achieves Pearson correlation coefficient of 0.733 and its mean absolute error of13.593. These prediction results provide valuable hints for revealing the structure and function of membrane *** Brain web server is free for academic use and available at ***/bioinf/Mem Brain/.

关键词： Transmembrane a-helices Structure prediction Machine learning Contact map prediction Relative accessible surface area

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：