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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31-40 订阅

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Comparing recurrent neural network with GARCH model on forecasting volatility based on SSE 50ETF 2

Comparing recurrent neural network with GARCH model on forec...

引用

2nd international conference on Statistics, Applied Mathematics, and computing science, CSAMCS 2022

作者： Luo, Yuanyuan Department of Statistics The London School of Economics and Political Science Houghton Street LondonWC2A 2AE United Kingdom

ISBN: (纸本)9781510663183

this paper compares the performance of DL models (RNN, LSTM and GRU) and GARCH model in three different train set, which with different time span. the data of empirical analysis is SSE 50ETF from 4th May 2010 to 26th Aug 2022. And the performance is compared with realized volatility. the result shows that SSE 50ETF is more relying on long historical information and pay less attention to new information. And in long periods, the DL models has better performance. However, the stability of DL models are significantly worse than GARCH model. the performance of DL models are highly relying on the selection of a train set. © 2023 SPIE.

关键词： Financial markets

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Fog based Edge Learning using IoT: Concepts, Challenges and Applications 4

Fog based Edge Learning using IoT: Concepts, Challenges and ...

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4th international conference on Smart Systems and Inventive Technology, ICSSIT 2022

作者： Sindhu, V. Sudhakaran, Pradeep Anitha, G. Mahendiran, P.D. Department of Information Technology Sri Krishna College of Engineering and Technology Coimbatore India Department of Computing Technologies School of Computing SRM Institute of Science and Technology Chengalpattu India Department of Information Technology Sri Shakthi Institute of Engineering and Technology Coimbatore India Department of Computer Science and Business Systems Sri Krishna College of Engineering and Technology Coimbatore India

ISBN: (纸本)9781665401180

In innovation world, fog and edge computing is extremely near the client which means making the processing capacities extremely nearer to the customer or user. the mushrooming of IoT devices and usage is increasing day by day. Huge amount of data will be generated by these connected devices. thus, there is an indispensable need to process such heavy volume of data in a quick and efficient manner. In request to meet the above standards. In this paper the research challenges of fog and Edge computing, the role of fog computing in IoT, the working model and benefits of edge computing are given in a novel approach after a de tailed review, study and scrutiny. this enables and paves way to the researcher for a smoother and sustainable research scope in the fog and edge computing environment. © 2022 IEEE

关键词： Fog computing

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Mammogram Image Classification Using Various Machine Learning Algorithms 7

Mammogram Image Classification Using Various Machine Learnin...

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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： Joshi, Arpita Mehta, Ashish Soban Singh Jeena University Department of Computer Science Almora India Kumaun University Department of Computer Science Nainital India

ISBN: (纸本)9798350309904

the leading cause of death in women is still breast *** cancer in its early stages is crucial. For the purpose of diagnosing breast cancer data, a variety of machine learning algorithms are *** this study, performance comparisons between different machine learning algorithms: Extra Trees, Random Forest, Support Vector Machine (SVM),Decision Tree, Logistic Regression Bagging, Gradient Boosting, and AdaBoost have been conducted on mammography images of MIAS(Mammographic Image Analysis Society) *** is observed that Bagging outperformed all other algorithms and achieved the highest accuracy (0.9678).All the work is done in the Kaggle environment based on the python programming language. © 2022 IEEE.

关键词： Adaptive boosting

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Network Powered by computing 4

Network Powered by Computing

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4th international science and Technology conference "Modern Network Technologies", MoNeTec 2022

作者： Smeliansky, Ruslan Moscow State University Dept. of Computational Mathematics and Cybernetics Moscow Russia

ISBN: (数字)9781665472463

ISBN: (纸本)9781665472463

the paper presents the concept of Network Powered by computing (NPC)-computing infrastructure, which is the convergence of data networks with computing installations like DC, Edge, HPC. this concept is based on an analysis of the properties of modern applications and the requirements for the computational infrastructure for them. the functional architecture of NPC and the main problems on the way of its feasibility are described. © 2022 IEEE.

关键词： Computer architecture Planning Convergence

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Detection Of Ships in Satellite Imagery Using Deep Neural Networks with Transfer Learning Approach 4

Detection Of Ships in Satellite Imagery Using Deep Neural Ne...

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

作者： Rutuparna, N. Indiramma, M. B.M.S. College of Engineering Department of Computer Science & Engineering Bengaluru India

ISBN: (纸本)9781665474368

With increasing trade and globalization of businesses, there is also an increasing need for an efficient, reliable and robust system for Naval Security, especially for a peninsular country like India. the developing technology and publicly available remote sensing data can be a great solution to this. the focus of this paper is to implement a Deep Neural Network model using transfer learning approach. © 2022 IEEE.

关键词： Remote sensing

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LCTU-Net: A U-Net with Lipschitz continuous Transformer for low-dose CT denoising 4

LCTU-Net: A U-Net with Lipschitz continuous Transformer for ...

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4th international conference on Advanced Algorithms and Neural Networks, AANN 2024

作者： Guo, Weizhen Yuan, Huaqiang Li, Yakang School of Computer Dongguan University of Technology Dongguan China Beijing China Spallation Neutron Source Science Center Dongguan China

ISBN: (纸本)9781510686106

Due to the constraints of reduced radiation doses, low-dose computed tomography (LDCT) images frequently suffer from increased noise levels. To address this challenge, we developed the LCTU-Net, a network that incorporates a Lipschitz continuous transformer to enhance the capability of feature extraction. this new approach replaces traditional Transformer components, improving the efficiency of loss reduction and achieving lower loss levels. the U-Net architecture integrated within LCTU-Net plays a crucial role in effectively reducing noise interference in the images. Experimental results have demonstrated that LCTU-Net significantly outperforms existing denoising technologies, particularly in its ability to preserve intricate image details while effectively reducing noise. © 2024 SPIE.

关键词： Computerized tomography

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4th international conference on Dynamic data Driven Applications Systems, DDDAS 2022

4th International Conference on Dynamic Data Driven Applicat...

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4th international conference on Dynamic data Driven Applications Systems, DDDAS 2022

ISBN: (纸本)9783031526695

the proceedings contain 42 papers. the special focus in this conference is on Dynamic data Driven Applications Systems. the topics include: Physics-Aware Machine Learning for Dynamic, data-Driven Radar Target Recognition;DDDAS for Optimized Design and Management of 5G and Beyond 5G (6G) Networks;DDDAS-Based Learning for Edge computing at 5G and Beyond 5G;monitoring and Secure Communications for Small Modular Reactors;data Augmentation of High-Rate Dynamic Testing via a Physics-Informed GAN Approach;unsupervised Wave Physics-Informed Representation Learning for Guided Wavefield Reconstruction;passive Radio Frequency-Based 3D Indoor Positioning System via Ensemble Learning;deep Learning Approach for data and computing Efficient Situational Assessment and Awareness in Human Assistance and Disaster Response and Battlefield Damage Assessment Applications;SpecAL: Towards Active Learning for Semantic Segmentation of Hyperspectral Imagery;generalized Multifidelity Active Learning for Gaussian-process-based Reliability Analysis;Multimodal IR and RF Based Sensor System for Real-Time Human Target Detection, Identification, and Geolocation;learning Interacting Dynamic Systems with Neural Ordinary Differential Equations;Relational Active Feature Elicitation for DDDAS;explainable Human-in-the-Loop Dynamic data-Driven Digital Twins;transmission Censoring and Information Fusion for Communication-Efficient Distributed Nonlinear Filtering;distributed Estimation of the Pelagic Scattering Layer Using a Buoyancy Controlled Robotic System;towards a data-Driven Bilinear Koopman Operator for Controlled Nonlinear Systems and Sensitivity Analysis;tracking Dynamic Gaussian Density with a theoretically Optimal Sliding Window Approach;dynamic data-Driven Digital Twins for Blockchain Systems;Adversarial Forecasting through Adversarial Risk Analysis Within a DDDAS Framework;essential Properties of a Multimodal Hypersonic Object Detection and Tracking System;power Grid Resilience: data Gaps for Da

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Comparative Study of Ransomwares 7

Comparative Study of Ransomwares

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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： Anand, Vivek Kumar Bamanjogi, Karunesh Shaw, Aryan Raj Faheem, Mahak NIIT University Computer Science and Engineering Neemrana India

ISBN: (纸本)9798350309904

Over the past few years cyberattacks have increased significantly as we have moved to a digital world. In 2021 this number rises drastically. Ransomware Attacks are not only limited to attacking an organization or a group of people to steal/encrypt their data, but it also refers to attacking networks or servers to slow down the services to such an extent thus creating the services unusable for the user, but at the same time, unlike other malware whose detection and analysis is not much complex, in ransomware, we find that they cannot be reverse engineered easily, due to high obfuscation and packing techniques involved. Skilled attackers are always a step ahead thus they find ways to evade the security systems or execute zero-day vulnerabilities. © 2022 IEEE.

关键词： Malware

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Improved algorithm of thermal image target detection based on Yolo v4 23

Improved algorithm of thermal image target detection based o...

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： Dong, Min Dang, Jia Sun, Gangcan Xue, Qi School of Information Engineering Zhengzhou University Zhengzhou City China Henan Institute of Advanced Technology Zhengzhou University Zhengzhou City China

ISBN: (纸本)9781665494571

As people have higher requirements for object detection accuracy and adaptability, this research proposes a single-stage algorithm for thermal image target detection based on Yolo v4. the algorithm combines the visible light image and the thermal image to complement the image information, and uses the TMDF (Two Modol Differential Fusion) module to perform feature fusion on the visible light image and the thermal image and then enter the network for training. Adding the DCT(Discrete Cosine Transform) adjustment network to adjust the final output can finally increase the mAP (mean Average Precision) value of the model on the KAIST data set by 3.7%, and MR (missed detection rate) value decreased by 3.5%. © 2021 IEEE.

关键词： Training Head Smart cities Fuses Lighting Object detection Transforms

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Research on data security sharing mechanism and application based on blockchain and privacy computing 4

Research on data security sharing mechanism and application ...

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4th international Academic Exchange conference on science and Technology Innovation, IAECST 2022

作者： Ma, Baoluo Chi, Cheng Tian, Juan Zhang, Yuwen China Academy of Information and Communications Technology Beijing China

ISBN: (纸本)9798350320008

the rapid growth and massive accumulation of various types of data have driven all walks of life to achieve high-quality development, and have had a major and profound impact on social governance and people's lives. However, there are many problems in the traditional data transaction and sharing, such as the loss of data ownership and the leakage of original data information. How to ensure the invisibility of data and the determination of data ownership while sharing data is an urgent problem. Based on this, combining the advantages of emerging technologies such as blockchain and privacy computing, this paper proposes a data security sharing architecture and mechanism based on blockchain and privacy computing to ensure the effective protection of personal information in the process of data sharing, to realize the safe circulation and sharing of data. © 2022 IEEE.

关键词： Blockchain

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