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IEEE Transactions on Artificial Intelligence 2022年第2期3卷 297-308页

作者： Zhang, Chongsheng Tao, Yuefeng Du, Kai Ding, Weiping Wang, Bin Liu, Ji Wang, Wei Henan Provincial Key Laboratory of Big Data Analysis and Processing Laboratory of the Yellow River Cultural Heritage Henan University Kaifeng475001 China School of Information Science and Technology Nantong University Nantong226019 China School of Electrical Engineering Zhejiang University Hangzhou310058 China Big Data Lab Baidu Inc. Beijing100044 China School of Computer and Information Technology Beijing Jiaotong University Beijing100044 China

Urban scenes are full of street entities with sign boards. Therefore, in autonomous driving, street view text spotting techniques will play a significant role in the precise understanding of surrounding scenes during driving, because texts contained in the images usually provide important clues for accurate image understanding, while it is often ambiguous for existing computer vision algorithms to understand scene images without texts. In this work, we propose a Multi-Segmentation network for character-level scene Text Detection (MSTD). The MSTD introduces a densely connected atrous spatial pyramid pooling module to enlarge the receptive field of the feature extraction layer, so as to localize long as well as large-sized text instances. Moreover, it devises a double segmentation subnetwork to utilize two independent but inherently complementary losses to co-optimize the network and increase the reliability of the confidence scores in predicting the text/nontext areas. With the character instances detected by the MSTD, one can easily perform scene text spotting with classic object recognition networks such as ResNet and DenseNet. We carried out extensive experiments on nine scene text datasets to demonstrate the outstanding performance of the MSTD on character-level and line-level text instance localization and scene text recognition, where the MSTD significantly outperforms the state-of-the-art scene text detection methods and the sequence-to-sequence-learning-based scene text recognizers. © 2020 IEEE.

关键词： Character recognition

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Heterogeneous Multi-Attribute Group Decision-Making Integrating Multi-Granulation Weighting Model and Improved VIKOR in Uncertain Linguistic Environment 9

Heterogeneous Multi-Attribute Group Decision-Making Integrat...

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9th International Conference on Fuzzy Systems and Data Mining, FSDM 2023

作者： Pang, Jifang Song, Peng Wang, Baoli Zhang, Chao Key Lab. of Computational Intelligence and Chinese Information Processing of Ministry of Education School of Computer and Information Technology Shanxi University Shanxi Taiyuan030006 China School of Economics and Management Shanxi University Shanxi Taiyuan030006 China School of Mathematics and Information Technology Yuncheng University Shanxi Yuncheng044000 China

ISBN: (纸本)9781643684703

Heterogeneous multi-attribute group decision-making (HMAGDM) is a complex decision-making problem that widely exists in the real world. However, there is relatively little research on the HMAGDM problems when the attribute set and alternative set are both heterogeneous, and the existing studies still have some limitations, such as the weight calculation is too simple, lacking objectivity and comprehensiveness;the ranking methods does not consider the utility of both group and individuals simultaneously, lacking flxibility and practicality. In order to obtain more effective decision results, a HMAGDM method integrating multi-granulation weighting model and improved VIKOR in uncertain linguistic environment is proposed in this paper. Our contributions can be identified as follows: (1) On the basis of the uncertainty and closeness of uncertain linguistic terms (ULTs), a measure indicator for the effectiveness of experts' opinions is proposed, and a finest-granulation weight optimization model for experts is established by maximizing the effectiveness;(2) Based on comprehensive consideration of effectiveness and deviation, a bi-objective optimization model is proposed to obtain the multi-granulation weights of attributes;(3) An improved VIKOR method combining the boundedness of ULTs and the multi-granulation weights of attributes is proposed to obtain more stable and effective ranking results. Finally, the case study and comparative analysis illustrate the feasibility and characteristics of the proposed method. © 2023 The authors and IOS Press.

关键词： Granulation

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Construction of a Sequence- and Backbone-Dependent Rotamer Library by Hidden-Markov Model

Construction of a Sequence- and Backbone-Dependent Rotamer L...

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International Conference on Bioinformatics and Biomedical Engineering (ICBBE)

作者： Wei Wen Qiang Qiang Lü Peng Yang Lingyun Yang Jinzhen Wu Xu Huang School of Computer Science and Technology Soochow University Suzhou China Information Processing Technology Jiangsu Provincial Key Lab for Computer Suzhou China

Sidechain prediction is an important subproblem of protein design and structure prediction. Construction of rotamer library is the basis for protein sidechain prediction because it provides the basic searching space for prediction. However, the state-of-the-art rotamer libraries focus on the statistical information of individual amino acids, ignoring the direct affection of its adjacent amino acids. This article presents a sequence- and backbone-dependent rotamer library. Both the conformation information of adjacent amino acids and torsion angle of the current residue are taken into account to construct a sequence- and backbone-dependent library by HMM. Evaluation on all 13 free modeling targets of CASP8 based on our rotamer library is conducted. Comparing with side-chain prediction based on the state-of-the-art rotamer library, our library outperforms the sidechain prediction accuracy on all the test targets to a certain extent.

关键词： Libraries Proteins Spine Amino acids Bayesian methods Hidden Markov models Predictive models Space technology Accuracy Statistical analysis

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Modified color co-occurrence matrix for image retrieval

Modified color co-occurrence matrix for image retrieval

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First International Conference on Natural Computation, ICNC 2005

作者： Chang, Min Hyuk Pyun, Jae Young Ahmad, Muhammad Bilal Chun, Jong Hoon Park, Jong An Dept. of Information and Communications Engineering Chosun University Gwangju Korea Republic of Signal and Image Processing Lab. Dept. of Mechatronics Gwangju Institute of Science and Technology Gwangju Korea Republic of Dept. of Computer Information and Communication Eng. Jeonnam Provincial Collage Jeonnam Korea Republic of

Color correlogram for content-based image retrieval (CBIR) characterizes not only the color distribution of pixels, but also the spatial correlation of pairs of colors. Color not only reflects the material of surface, but also varies considerably with the change of illumination, the orientation of the surface, and the viewing geometry of the camera. The invariance to these environmental factors is not considered in most of the color features in color based CBIR including the color correlogram. However, pixels changed their color with almost same proportions with change of environmental factors. This fact is taken into consideration, and new algorithm is proposed. The color cooccurrence matrix for different spatial distances is defined based on the maximum/minimum of color component between the three components (R,G,B) of a pixel. The proposed algorithm has less number of features, and the change of illumination, etc. is also taken into account. © Springer-Verlag Berlin Heidelberg 2005.

关键词： Image retrieval

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Combining opportunistic routing with dynamic source routing for wireless mesh networks

Combining opportunistic routing with dynamic source routing ...

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Institution of Engineering and technology International Communication Conference on Wireless Mobile and Computing

作者： Shen, Qiang Fang, Xuming Kim, Sunmyeng He, Rong Provincial Key Lab. of Information Coding and Transmission Southwest Jiaotong University Chengdu 610031 China High Performance Network Lab. Institute of Acoustics Chinese Academy of Sciences Beijing 100190 China School of Computer and Software Engineering Kumoh National Institute of Technology Gyeongbuk 730701 Korea Republic of

ISBN: (纸本)9781849191388

Routing in wireless mesh networks presents a great challenge due to unreliable wireless links and collisions. Recently, a new routing method, opportunistic routing (OR), is proposed to deal with them by exploiting broadcast nature of wireless networks. OR relies on the global knowledge of networks to select relays and determine priorities. In this paper, we propose a new routing scheme, OxDSR, which combines OR and dynamic source routing (DSR) and performs opportunistic transmissions with the help of the local information and the traditional route obtained by DSR. By taking the duplicates and additional wireless resource consumed by multiple ACK frames into consideration, we propose a new metric, equivalent data rate, to select and prioritize relays. Extensive simulation study shows that the proposed OxDSR is more resilient and achieves higher throughput than DSR based on the expected transmission count routing metric.

关键词： Medium access control

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Kinetics and Modeling of Chemical Leaching of Sphalerite Concentrate Using Ferric Iron in a Redox-controlled Reactor

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Chinese Journal of Chemical Engineering 2013年第8期21卷 933-936页

作者：宋健高玲林建群吴洪斌林建强 State Key Lab of Microbial Technology Shandong University Department of Pharmacy and Biotechnology Zibo Vocational Institute Shandong Provincial Key Lab for Distributed Computer Software Novel Technology School of Information Science and EngineeringShandong Normal University Institute of Agro-products Processing Science and Technology Xinjiang Academy of Agricultural and Reclamation Science

This work presents a study for chemical leaching of sphalerite concentrate under various constant Fe3+ concentrations and redox potential conditions. The effects of Fe3+ concentration and redox potential on chemical leaching of sphalerite were investigated. The shrinking core model was applied to analyze the experimental results. It was found that both the Fe3+ concentration and the redox potential controlled the chemical leaching rate of sphalerite. A new kinetic model was developed, in which the chemical leaching rate of sphalerite was proportional to Fe3+ concentration and Fe3+ /Fe2+ ratio. All the model parameters were evaluated from the experimental data. The model predictions fit well with the experimental observed values.

关键词： sphalerite leaching kinetic model Fe3+ concentration redox potential lab.IEW

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A Resource Matching Algorithm for Dynamic Multi-Homing Service Environment 2

A Resource Matching Algorithm for Dynamic Multi-Homing Servi...

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2nd IEEE Advanced information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2018

作者： Zhang, Hui Liu, Shu Nanjing University of Posts and Telecommunications Jiangsu Key Lab of Wireless Communications Nanjing China National Engineering Research Center of Communications and Networking Nanjing University of Posts and Telecommunications Nanjing210003 China Provincial Key Laboratory for Computer Information Processing Technology Soochow University Suzhou215006 China

ISBN: (纸本)9781538618035

T43 paper investigates the matching problem between radio resources and multi-homing services in a dynamic heterogeneous wireless environment. A mobile terminal (MT) with multi-homing service simultaneously transmits data to multiple radio access networks using multiple air interfaces. We develop an energy efficient resource matching algorithm for statistically guaranteeing the transmission rate of each MT with the minimum power consumption. Firstly, aided with the resource matching conception and the dynamic characteristics of wireless channels, we propose a matching probability metric to construct resource matching model for maximizing energy efficiency of all MTs subject to statistical guarantee requirements, and simplify the dynamic channels characteristic based on matching theory. Secondly, we propose a two-level distributed matching algorithm (TLDMA), with inner minimum power consumption and outer maximum matching probability, which realizes joint optimal allocation of bandwidth, transmission power and rate. Simulation results show that TLDMA outperforms conventional algorithms in terms of wireless resources management. © 2018 IEEE.

关键词： Energy efficiency

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AUCSeg: AUC-oriented Pixel-level Long-tail Semantic Segmentation 38

AUCSeg: AUC-oriented Pixel-level Long-tail Semantic Segmenta...

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38th Conference on Neural information processing Systems, NeurIPS 2024

作者： Han, Boyu Xu, Qianqian Yang, Zhiyong Bao, Shilong Wen, Peisong Jiang, Yangbangyan Huang, Qingming Key Lab. of Intelligent Information Processing Institute of Computing Technology CAS China School of Computer Science and Tech. University of Chinese Academy of Sciences China Peng Cheng Laboratory China Key Laboratory of Big Data Mining and Knowledge Management CAS China

The Area Under the ROC Curve (AUC) is a well-known metric for evaluating instance-level long-tail learning problems. In the past two decades, many AUC optimization methods have been proposed to improve model performance under long-tail distributions. In this paper, we explore AUC optimization methods in the context of pixel-level long-tail semantic segmentation, a much more complicated scenario. This task introduces two major challenges for AUC optimization techniques. On one hand, AUC optimization in a pixel-level task involves complex coupling across loss terms, with structured inner-image and pairwise inter-image dependencies, complicating theoretical analysis. On the other hand, we find that mini-batch estimation of AUC loss in this case requires a larger batch size, resulting in an unaffordable space complexity. To address these issues, we develop a pixel-level AUC loss function and conduct a dependency-graph-based theoretical analysis of the algorithm's generalization ability. Additionally, we design a Tail-Classes Memory Bank (T-Memory Bank) to manage the significant memory demand. Finally, comprehensive experiments across various benchmarks confirm the effectiveness of our proposed AUCSeg method. The code is availab.e at https://***/boyuh/AUCSeg. © 2024 Neural information processing systems foundation. All rights reserved.

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Automatic diagnosis of disc herniation based on DenseNet fusion model 8

Automatic diagnosis of disc herniation based on DenseNet fus...

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8th International Conference on Digital Home, ICDH 2020

作者： Wang, Zimin Qin, Junyan Huang, Jinrong Wang, Yumeng Li, Ji Guilin University of Electronic Technology Guangxi Colleges and Universities Key Lab. of Intelligent Processing of Computer Image and Graphics Guilin541004 China Guilin Huigu Institute of Artificial Intelligence Industrial Technology Guilin541004 China Guilin University of Electronic Technology School of Computer Science and Information Security Guilin541004 China

ISBN: (纸本)9781728192345

Spine MRI images generally have the characteristics of low contrast and much noise. Because the variable shape of the spine edge, the traditional spine image segmentation method requires a lot of preprocessing and can not perform image segmentation automatically, which is inefficient and cannot compliant the clinical work requirements. So as to solve the above problems, this paper use deep learning algorithms to identify the spine images, and proposed a disc herniation recognition method for spinal MRI images which based on DenseNet fusion model. Use DenseNet and Inception-Resnet-V2 model fusion to get more image features and improve the image recognition accuracy. Experiments prove that this method can be used to identify the herniation of spinal intervertebral disc with high accuracy and real-time. © 2020 IEEE.

关键词： Image segmentation

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Positional translation language model for ad-hoc information retrieval

Positional translation language model for ad-hoc information...

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18th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2014

作者： Tu, Xinhui Luo, Jing Li, Bo He, Tingting Gu, Jinguang College of Computer Science and Technology Wuhan University of Science and Technology Wuhan China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan China Department of Computer Science Central China Normal University Wuhan China State Key Lab. of Software Engineering Wuhan University Wuhan China

ISBN: (纸本)9783319066042

Most existing language modeling approaches are based on the term independence hypothesis. To go beyond this assumption, two main directions were investigated. The first one considers the use of the proximity features that capture the degree to which search terms appear close to each other in a document. Another one considers the use of semantic relationships between words. Previous studies have proven that these two types of information, including term proximity features and semantic relationships between words, are both useful to improve retrieval performance. Intuitionally, we can use them in combination to further improve retrieval performance. Based on this idea, this paper propose a positional translation language model to explicitly incorporate both of these two types of information under language modeling framework in a unified way. In the first step, we present a proximity-based method to estimate word-word translation probabilities. Then, we define a translation document model for each position of a document and use these document models to score the document. Experimental results on standard TREC collections show that the proposed model achieves significant improvements over the state-of-the-art models, including positional language model, and translation language models. © 2014 Springer International Publishing.

关键词： information retrieval

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