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检索条件"任意字段=2009 2nd International Conference on Intelligent Computing Technology and Automation, ICICTA 2009"

共 205 条记录，以下是1-10 订阅

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Fast Image matting based on matting pyramids and surrogate models 2

Fast Image matting based on matting pyramids and surrogate m...

引用

2nd international conference on Robotics, Artificial Intelligence and intelligent Control, RAIIC 2023

作者： Liang, Yihui Gou, Hongshan Liu, Guisong Huang, Sibo University of Electronic Science and Technology of China School of Computer Science and Engineering Chengdu China University of Electronic Science and Technology of China Zhongshan Institute School of Computer Zhongshan China Guiyang Institute of Humanities and Technology College of Big Data and Information Engineering Guiyang China Southwestern University of Finance and Economics School of Computing and Artificial Intelligence Chengdu China Huizhou University Network and Information Centre Huizhou China

ISBN: (纸本)9798350328004

Image matting is a foundation task in the field of computer vision. Pixel-pair-optimization-based image matting methods have attracted lots of attention due to their distinct advantages on parallelization and handling spatially disconnected foregrounds. However, these methods struggle when the computing time is limited. To address this issue, this study presents the image matting method based on matting pyramid and surrogate model (IMMPSM). IMMPSM speeds up the process of pixel pair optimization by replaces the evolutionary algorithm in the pyramid matting framework, which consumes a lot of computing time, with the efficient surrogate-model-based method. The constructed surrogate model is reused by the presented surrogate model share strategy to save computing time. Specifically, the constructed surrogate model is shared with the pixel pair optimization subproblem adjacent to current subproblem avoiding repeated computation on the surrogate model construction. Extensive experimental results show that IMMPSM can provide acceptable alpha mattes even under limited computing time. © 2023 IEEE.

关键词： Pixels

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A Supervised Model to Detect Suspicious Activities in the Bitcoin Network 2nd

A Supervised Model to Detect Suspicious Activities in the Bi...

引用

2nd international conference on Emerging Technologies and intelligent Systems, ICETIS 2022

作者： Al-Hashedi, Khaled Gubran Magalingam, Pritheega Maarop, Nurazean Samy, Ganthan Narayana Rahim, Fiza Binti Abdul Shanmugam, Mohana Hasan, Mohammad Kamrul Advanced Informatics Department Razak Faculty of Technology and Informatics Universiti Teknologi Malaysia Kuala Lumpur Malaysia College of Computing and Informatics Universiti Tenaga Nasional Malaysia Selangor Kajang43000 Malaysia Center for Cyber Security Faculty of Information Science and Technology Universiti Kebangsaan Malaysia Selangor Bangi43600 Malaysia

ISBN: (纸本)9783031252730

Shortly after its official launch in 2009, Bitcoin has gained rapid popularity worldwide, which in return attracted a variety of people especially malicious attackers, who get the advantage of its pseudo-anonymity to institute un-traceable threats, scams, and criminal activities. Recently, some Bitcoin thefts have been reported costing millions of dollars, causing serious harm and losses to innocent users or companies that lead them to declare bankruptcy. One of the main characteristics of Bitcoin is its anonymity, which makes Bitcoin the preferred choice for criminals to perform illicit activities that pose difficulties for law enforcement and financial authorities to identify suspicious behavior, making the existing fraud detection systems ineffective. In this paper, we propose a model for detecting suspicious activities in the Bitcoin network. We first construct a labeled dataset by collecting a set of illicit transactions from public online Bitcoin forums, as well as datasets from prior research. Next, a verification and filtration process has been performed to verify the gathered illicit transactions with the original dataset and manually marked them as either legal or illegal. Additionally, a new set of features that are based on time-slice was extracted, the skewed dataset was balanced, and three supervised classifiers (LR, NB, and ANN) were used for evaluating the proposed model. Finally, our findings found that the ANN classifier achieved the best performer among others, which attained Precision, Recall, F1 scores, and AUC of 95.2%, 88.7%, 89.8%, and 91.2% respectively. The performance of the supervised classifiers has significantly improved after balancing the training set. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Machine learning

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Comparative Sentiment Analysis on Stock Market News Using Machine Learning 1

引用

2nd international conference on intelligent computing Techniques for Smart Energy Systems, ICTSES 2021

作者： Sachar, Devansh Goyal, Hemlata Sharma, Vijay Kumar Department of Computer and Communication Engineering School of Computing and Information Technology Manipal University Jaipur Rajasthan Jaipur India

ISBN: (数字)9789811902529

ISBN: (纸本)9789811902512

The forecasting of the stock market values particularly the multi-national firms is a truly intriguing and thought provoking task. Sentiment Analysis instigates many companies to conduct market survey, competitive analysis and gain an edge in their respective industry along with expedite the process to understand the future trends of stock news data. In the context of sentiment analysis, top 25 economic news and reddit reviews are taken for sentiment analysis using natural language processing for this work. The dataset is taken downfallen stock range (2000–2008) and uplifting stock range (2009–2016), in two slots. We examine machine learning classifiers of Random Forest, Multi Binomial Naïve Bayes, Passive Aggressive and Linear Regression individually for training–testing with accuracy measures of the sentimental data. Sentimental data is extracted with the N-gram and TF-IDF vectorization to evaluate the sentiment accuracy in changing the stock of the particular period. On the basis of Performance Measures for Random Forest, Multi Binomial Naïve Bayes, Passive Aggressive and Linear Regression machine learning models, a very less considerable difference is measured. Among all the machine learning models, Random Forest classifier is selected as best classifier with 85.97% accuracy and ±1.0 error in terms of the effect of emotional values with respect to stock market values by the performance matrices. The obtained performance accuracy of all the applied models is more than 83% in all. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Sentiment analysis

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Custom Block Chain Based Cyber Physical System for Solid Waste Management 2nd

Custom Block Chain Based Cyber Physical System for Solid Was...

引用

2nd international conference on Recent Trends in Advanced computing, Disruptive Innovation (ICRTAC-DTI)

作者： Thada, Ayush Kapur, Uday Karan Gazali, Saif Sachdeva, Nikhil Shridevi, S. Vellore Inst Technol Chennai Tamil Nadu India

The aim of this paper is to develop an intelligent cyber-physical system for the waste management in a locality which will not only keep records of the use of the trash bins in the but also ensure they have an additional blockchain based verification system which will ensure the proper working even in the presence of an adversary. The proposed system is an ensemble of the database server, blockchain server, embedded system based clients and an android app. This is inspired by the recent global trend in smartphone popularity which has piqued interest in the above mentioned division. The advent of smartphone popularity helps us to create an ideal system for a plethora of reasons such as processing capability and native storage etc. Furthermore, blockchain technology, introduced by Satoshi Nakamoto in 2009 ensures decentralization and security of transactions due to its use of cryptographic hash functions and public key cryptographic system. To further excite the situation, India recently revised its solid waste management policy in 2016 after 16 long years. All of the above factors together pointed to creation of a smart waste management system to prevent further exacerbation of India's existing waste management crisis. (C) 2019 The Authors. Published by Elsevier B.V.

关键词： cyber-physical systems blockchain solid waste management embedded systems intelligent systems

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A Dynamic Community Detection Algorithm Based on Parallel Incremental Related Vertices 2

A Dynamic Community Detection Algorithm Based on Parallel In...

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2017 IEEE 2nd international conference on Big Data Analysis（ICBDA 2017）

作者： Guohui Li Kun Guo YuZhong Chen Ling Wu Danhong Zhu College of Mathematics and Computer Sciences Fuzhou University Fujian Provincial Key Laboratory of Network Computing and Intelligent Information Processing(Fuzhou University) Key Laboratory of Spatial Data Mining & Information Sharing Ministry of Education

ISBN: (纸本)9781509036202

One of the traditional ways for detecting dynamic communities is to find the communities at each interval through the static community detection ***,it usually leads to high computation *** this paper,a novel algorithm based on the Map Reduce model and the label propagation progress with the strategy of incremental related vertices is proposed,which is called PLPIRV(Parallel Label Propagation and Incremental Related Vertices).Based on the communities found at the previous interval,the new algorithm adjusts the communities the incremental related vertices belong *** clustering of the whole network can be avoided by incrementally analyzing the variation of the networks,so that the time cost can be greatly *** on artificial and real datasets show that the proposed algorithm performs well on dynamic community detection.

关键词： dynamic community detection parallel computation incremental algorithm label propagation

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2009 2nd international conference on intelligent computing technology and automation, icicta 2009

2009 2nd International Conference on Intelligent Computing T...

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2009 2nd international conference on intelligent computing technology and automation, icicta 2009

ISBN: (纸本)9780769538044

The proceedings contain 889 papers. The topics discussed include: a delay decomposition approach to stability of linear neutral systems with mixed delays;a joint evolutionary method based on neural network for feature selection;a new early stopping algorithm for improving neural network generalization;an HLA based design of collision simulation system for large-scale LEO objects;an optimization model on the radiation area of the international inland port;computer simulation of grout flowing in intermittent fractured network;dynamic change in landscape pattern of Shen-fu connection area based on Markov model;an approach for fully integrated automation in heterogeneous industrial control network;analysis of the bargain power under clean development mechanism with game theory;research on collaborative design based on web services and agent technology;and research on multi-agent decision-making model of wind-solar complementary power generation system.

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2009 2nd international conference on intelligent computing technology and automation, icicta 2009

2009 2nd International Conference on Intelligent Computing T...

引用

2009 2nd international conference on intelligent computing technology and automation, icicta 2009

ISBN: (纸本)9780769538044