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检索条件"任意字段=4th International Conference on Computing and Data Science, CONF-CDS 2022"

共 1120 条记录，以下是121-130 订阅

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A Deep Learning Approach in Detection of COVID-19 Positive Patients using CT Scan Images 4

A Deep Learning Approach in Detection of COVID-19 Positive P...

引用

4th international conference on Inventive Research in computing Applications, ICIRCA 2022

作者： Sharma, Suraj Singh, Ranjeet Kumar Madhav Institute of Technology and Science Gwalior Dept. of Computer Science & Engineering Gwalior India

ISBN: (数字)9781665497077

ISBN: (纸本)9781665497077

this paper presents a method for evaluating the utility of deep transfer learning in the development of a classifier for detecting COVID-19 positive patients using CT scan images. Deep Learning (DL) is good at detecting COVID-19 cases, according to the research. For expanding the training dataset to reduce overfitting and improve the model's generalization capacity data augmentation approach is employed. the proposed study has evaluated a set of pretrained deep neural networks for Convolutional Neural Network (CNN). the suggested model used DenseNet with Res Net and a two-layer CNN model which gives better performance. the proposed model gives efficient results with the training and testing accuracy of 0.98 and 0.96. © 2022 IEEE.

关键词： COVID-19

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Qualitative Analysis of Anomaly Detection in Time Series 4

Qualitative Analysis of Anomaly Detection in Time Series

引用

4th international conference on Circuits, Control, Communication and computing, I4C 2022

作者： Bhat, Mohammad Qazim Alex, Sini Anna Nanda, Simran Goutham, Sevanthi Ramaiah Institute of Technology Department of Computer Science & Engineering Bengaluru India

ISBN: (纸本)9798350397475

We present an end-end system for time series anomaly detection specifically aimed at detecting fraudulent transactions in bank transaction datasets. the goal of anomaly detection is to locate unusual or uncommon occurrences in data. Outlier detection, one of the most crucial data analysis jobs, has many practical uses. For instance, in order to track their company data and send out notifications for outliers, Yahoo and Microsoft have developed their own services for time-series outlier identification. However, majority of outlier identification methods employ classifications of unusual entries without providing any justification. therefore, the goal is to make the anomalous points as predicted by the model more interpretable and thereby create a flagging system to help human labelers in determining anomalous behavior. this will help reduce human engineering efforts by a huge margin. © 2022 IEEE.

关键词： data mining

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A comparative analysis of stock price prediction techniques 7

A comparative analysis of stock price prediction techniques

引用

7th international conference on computing, Communication and Security, ICCCS 2022 and 2022 4th international conference on Big data and Computational Intelligence, ICBDCI 2022

作者： Singh, Kuldeep thapliyal, M.P. Barthwal, Varun H.N.B. Garhwal University Department of Computer Science and Engineering GarhwalUttarakhand Srinagar India

ISBN: (纸本)9798350309904

Stock index futures are difficult to forecast due to unpredictable stock market conditions. Despite this fact, efforts are being made over the years to create an efficient forecasting tool. the current advancements in technology like machine learning and artificial intelligence have improved our performance with non-linear estimation. Here, the non-linear, RNN (Recurrence Neural Networks)-based stock index prediction model has been compared to the linear, technical indicator-based stock index prediction model. In our empirical research, ten years of day-wise close price data of Tata Consultancy Services Ltd has been used. the study explores two separate methods for predicting stock prices, each coming from a distinct specialty: In the linear model, MA (moving average) and EMA (exponential moving average) model, and the nonlinear model LSTM (long short-Term memory) approach has been used. the analysis shows that when it comes to stock price prediction, the exponential moving average outperforms the LSTM. © 2022 IEEE.

关键词： Long short-term memory

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Organs-At-Risk Segmentation in Medical Imaging Based on the U-Net with Residual and Attention Mechanisms 23

Organs-At-Risk Segmentation in Medical Imaging Based on the ...

引用

23rd IEEE international conference on High Performance computing and Communications, 7th IEEE international conference on data science and Systems, 19th IEEE international conference on Smart City and 7th IEEE international conference on Dependability in Sensor, Cloud and Big data Systems and Applications, HPCC-DSS-SmartCity-DependSys 2021

作者： Lin, Xiao-Wei Li, Ni Qi, Qi School of Computer Science and Technology Hainan University Haikou China School of Mathematics and Statistics Hainan Normal University Hainan Normal University Key Laboratory of Data Science and Intelligence Education of Ministry of Education Haikou China

ISBN: (纸本)9781665494571

In this paper, we proposed a new organs-at-risk segmentation method for Medical images of heads and necks based on the U-Net with residuals and attention mechanism. A Project & Excite (PE) block combined with a residual method is proposed as Residual-PE Block in the U-Net encoding stage in order to enhance the feature expression ability. Attention Gates (AGs) are introduced in the decoding stage to increase the relevance of feature weighting in accord with segmentation tasks. the proposed method has been evaluated through a set of real world medical images including 22 organs at risk in the head and neck. Experimental results showed that our proposed method improved the average segmentation accuracy by 3-4% compared with current existing methods. the average Dice Similarity Coefficient (DSC) score on the segmentation of the 22 types of head-and-neck related organs at risk is 79.5% and the average 95% Hausdorff Distance (HD) is 6.99mm. It demonstrates that this approach is promising for clinical doctors to improve their accuracy and efficiency in radiotherapy. © 2021 IEEE.

关键词： Image segmentation Head three-dimensional displays Smart cities Medical services Logic gates Encoding

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Research on Cache Algorithm for Internet of Vehicles Based on Edge computing 4

Research on Cache Algorithm for Internet of Vehicles Based o...

引用

4th international conference on Frontiers Technology of Information and Computer, ICFTIC 2022

作者： Wang, Xuechun Chen, Guifen School of Electronic and Information Engineering Changchun University of Science and Technology Changchun China

ISBN: (纸本)9798350321951

A huge number of computational resource-intensive applications and other content delivery services have evolved with the arrival of the 5G era and the adoption of Internet-connected devices, and the data in the Internet of Vehicles has exhibited accelerated growth. To improve the service performance of telematics, caching content at the network edge is an effective solution to reduce content delivery latency. In this paper, we propose an edge caching scheme based on content popularity with cooperation between base stations, roadside units(RSUs) and vehicles, and use an improved sparrow search algorithm(PSSA)for optimization. Simulations show that the proposed caching scheme has advantages in terms of hit rate improvement and delay reduction. © 2022 IEEE.

关键词： Edge computing

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Quantum computing and Quantum Machine Learning Classification - A Survey 4

Quantum Computing and Quantum Machine Learning Classificatio...

引用

4th international conference on Cybernetics, Cognition and Machine Learning Applications, ICCCMLA 2022

作者： Kuppusamy, P. Kumar, Nnvs Yaswanth Dontireddy, Jyotsna Iwendi, Celestine VIT-AP University School of Computer Science and Engineering Andhra Pradesh Amaravati India University of Bolton School of Creative Technologies United Kingdom

ISBN: (数字)9781665462464

ISBN: (纸本)9781665462464

the rapid development of machine learning technology leads to make the devices in the industries working autonomously. However, the growth of sensors in the industries leads to produce vast data that is utilized by machine learning algorithms to improve the autonomous devices' performances. However, classical ML algorithms and hardware systems cannot process large data to meet real-time problems. Hence, the researchers have developed Quantum computing hardware systems and Quantum Machine learning algorithms to speed up the process. this research work presented the review of quantum computing mechanisms and QML algorithms that are applied to classify the images. this work demonstrated the performance comparison of various QML algorithms. It showed that the images are classified using various QML algorithms faster than classical ML algorithms in terms of time. © 2022 IEEE.

关键词： Learning algorithms

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Supply Chain Construction and Optimization Model Based on Grid computing and Process data Mining Algorithms 4

Supply Chain Construction and Optimization Model Based on Gr...

引用

4th international conference on Inventive Research in computing Applications, ICIRCA 2022

作者： Xie, Meie Wuhan Business University Logistics Management Research Labs Hubei WuHan430000 China

ISBN: (数字)9781665497077

ISBN: (纸本)9781665497077

this paper studies the supply chain construction and optimization model based on grid computing and process data mining algorithms. C2B supply chain management mode causes enterprises to rely too much on suppliers. In order to get rid of dependence on suppliers and establish partnerships with more suppliers is an effective way for e-commerce enterprises to reduce business risks, and selecting capable suppliers has a certain positive effect on promoting the overall function of the supply chain. Hence, in this paper, the model is based on this and the computin model is integrated. Using grid computing technology to the connect computers all over the world, and integrate computer resources all over the world into fully shared resources through high-speed Internet, can be said to be a new change based on supercomputer and Internet technology. the integration model is tested and verified from different aspects. © 2022 IEEE.

关键词： data mining

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Ledger-based Electronic Voting System using a multi-tier security approach 4

Ledger-based Electronic Voting System using a multi-tier sec...

引用

4th international conference on Emerging Research in Electronics, Computer science and Technology, ICERECT 2022

作者： Chatterjee, Aniruddha Sidhu, Sanah Jebakumar, R. SRM Institute of Science and Technology Computing Technologies Chennai India

ISBN: (纸本)9781665456357

the right to vote is one of the fundamental tenets upon which democracies are built. the voting process has several difficulties in the modern day due to the prevalence of digital technology. By developing a prototype application that makes use of the idea of a ledger-based data store on a blockchain and a graph database, the purpose of this paper is to search for a workable answer to the problems of security, accessibility, and transparency in the electoral process, in an effort to identify an answer that is best suited and adaptable on a large scale. A distributed ledger uses linked nodes to store data in such a way that once a block is written, it cannot be modified on the chain without compromising the chain's integrity and the trust that users have placed in it. this property of blockchain is utilised by us in developing a secure data store for the application. © 2022 IEEE.

关键词： Graph databases

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Intelligent Transport System using Cloud computing and PSY Key Generation for V2V Communication 4

Intelligent Transport System using Cloud Computing and PSY K...

引用

4th international conference on Cognitive computing and Information Processing, CCIP 2022

作者： Kumar K, Prdeep Itagi, Salma Nagarathna, C. Ashwini, S.S. Srinidhi, N.N. Bengaluru560064 India Sai Vidya Institute of Technology Department of Computer Science and Engineering VTU Rajanukunte Bengaluru560064 India Sai Vidya Institute of Technology Department of Information Science and Engineering VTU Rajanukunte Bengaluru560064 India Manipal Institute of Technology Bengaluru Department of Computer Science and Engineering Manipal Academy of Higher Education Manipal India

ISBN: (纸本)9781665456487

the Internet of things (IoT) connects many sensors to the internet so that it will provide services and applications for smart cities. Vehicles connected to the internet can communicate, sense, analyze and also make decision on their own. Vehicular Cloud (VC) is new idea proposed to enhance vehicular services through mobile cloud computing and networking. this proposed paper highlights an Intelligent Transportation System (ITS) which provides creative applications and services related to traffic management and also to access the information for various users. A model is developed taking picture of vehicles in detail, time of availability of vehicle in a given region. A new paradigm to collect the data for tracking the intelligent system in vehicular communication is considered. the simulation results are produced regarding involvement of vehicles in low percentage in dynamic VCN which provides data for intelligent system. © 2022 IEEE.

关键词： Vehicles

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A Survey of Machine learning algorithms for Lung cancer detection 4

A Survey of Machine learning algorithms for Lung cancer dete...

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4th international conference on Advances in computing, Communication Control and Networking, ICAC3N 2022

作者： Kukreja, Sonia Sabharwal, Munish Gill, D.S. Galgotias University Scse Greater Noida India Gwangju Institute of Science and Technology School of Electrical Engineering and Computer Science Korea Republic of

ISBN: (纸本)9781665474368

Cancer has the highest mortality rate and the succeeding most regular found cancer is lung cancer in both men and women. Various tests are carried out to detect lung cancer and some of them are expensive and risky for the human being. In this paper various techniques discovered for the early detection of lung cancer have been presented, in which electrical nose technology is effective giving the 0.8871 accuracy & G-mean is 0.8676. Some researchers had taken 1st stage patients' data while some had considered the 2nd stage. Various hybrid techniques are with Machine Learning algorithms. © 2022 IEEE.

关键词： Diseases

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