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检索条件"任意字段=11th International Conference on Intelligent Data Engineering and Automated Learning"

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Construction of an intelligent Teaching Information Management Cloud Platform Based on Mobile Information Technology 11th

Construction of an Intelligent Teaching Information Manageme...

引用

11th international conference on Applications and Techniques in Cyber Intelligence, ATCI 2023

作者： Li, Qian Liu, Kai Chen, Xiaoning Finance office Shandong Institute of Commerce and Technology Shandong Jinan250031 China

the proposal of student teaching information management conforms to the requirements of the times, which makes cloud platform technology and internet information processing particularly important. In order to keep up with the needs of the public, education and teaching management needs in-depth research. the analysis of student teaching information management can improve the monitoring of students' learning ability and physical and mental health from multiple aspects, contributing to providing a good student talent environment. this article introduced the design of a student teaching information management cloud platform based on mobile internet. this platform utilized cloud computing technology and mobile internet technology to achieve online management and sharing of student teaching information. the platform has functions such as user management, course management, grade management, and online communication, making it easy to manage and analyze students' teaching information, improving the quality and efficiency of school teaching. this article applied experimental and comparative methods to analyze the performance and functionality of the teaching information management system. the experimental data showed that the accuracy of the score query function in the system ranked first, reaching 99.92%, and the availability was 99.54%. © 2024 the Authors. Published by Elsevier B.V.

关键词： Cloud platforms

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Time-Based Distributed Collaborative Filtering Recommendation Algorithm 1

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11th European-Alliance-for-Innovation (EAI) international conference on Mobile Networks and Management (MONAMI)

作者： Li, Qiao Hu, Xiantong Zhou, Linfei Zheng, Xiao Zhao, Wei Gao, Yunquan Wu, Xuangou AnHui Univ Technol Sch Comp Sci & Technol Maanshan 243032 Peoples R China Inst Artificial Intelligence Hefei Comprehens Natl Sci Ctr Hefei 230026 Peoples R China AnHui Univ Technol Anhui Engn Lab Intelligent Applicat & Secur Ind I Maanshan 243032 Peoples R China

ISBN: (数字)9783030947637

ISBN: (纸本)9783030947637;9783030947620

Recommendation systems based on collaborative filtering are widely used in many fields. Alternating Least Squares (ALS) in the Mlib Library is a distributed and parallel algorithm in Spark framework, which can solve the problems of scalability and speedup in a limited hardware resources of stand-alone systems. However, it does not consider the influence of the factor of time on the recommendation accuracy. Taking restaurant ratings as an example, this month ratings are more reliable than those from last year. thus, the motivation in our proposal re-scores ratings with different time weights. We improve ALS in its process of data preparation according to requirements on the structure of data input. Consequently, our improvement does not need to modify the main body of ALS. Experimental results validate effectiveness that our proposal outperforms the original ALS in recommendation accuracy.

关键词： Collaborative filtering ALS Time factor RMSE

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A Brief Survey on Semantic-preserving data Augmentation 11

A Brief Survey on Semantic-preserving Data Augmentation

引用

11th international conference on Information Technology and Quantitative Management, ITQM 2024

作者： Song, Shaoyue Zhu, Qing Miao, Zhenjiang Department of Software Engineering Beijing University of Technology Beijing100124 China Institute of Information Science Beijing Jiaotong University Beijing100044 China

In the era of deep learning, it's important to obtain enough qualified data for model training. For the labor-intensive and time-consuming characteristics of data collection and annotation, date augmentation has been widely employed in deep learning methods to mitigate over-fitting. It has been proven to be one of the most effective ways to ensure the performance of deep models. In the field of computer vision, the principal goal of data augmentation usually is enlarging both the scale and diversity of the dataset, and maintaining the quality of both the image and the annotation data simultaneously. data augmentation methods at the raw input data level are intuitive to obtain semantic meaningful images. In this paper, we provide a brief survey on some data augmentation studies conducted at image level and briefly categorize the studies into two main classes: those based on image editing and those based on image generation. We also make an analysis of the semantic-preserving considerations within data augmentation techniques. © 2024 the Authors.

关键词： Computer Vision data Augmentation Semantic-preserving

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Change detection in synthetic aperture radar images based on fuzzy restricted Boltzmann machine 11th

Change detection in synthetic aperture radar images based on...

引用

11th international conference on Bio-inspired Computing – theories and Applications, BIC-TA 2016

作者： Li, Na Shi, Jiao Gong, Maoguo School of Electronics and Information Northwest Polytechnical University 127 West Youyi Road Xi’anShaanxi710072 China Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China Xidian University 2 South TaiBai Road Xi’anShaanxi710071 China

ISBN: (纸本)9789811036101

Image Change Detection is a process to identify the changes of two images of the same scene that were taken in different times. In this paper, we propose a novel change detection approach based on Fuzzy Restricted Boltzmann Machine. the approach applies Fuzzy Restricted Boltzmann Machine as unsupervised feature learning algorithm and Fuzzy Back Propagation as supervised fine-tuning algorithm. Fuzzy Restricted Boltzmann Machine applying to change detection can reduce the effect of speckle noise in Synthetic Aperture Radar Images, in which the parameters governing the model are replaced by fuzzy numbers. Experiments on real data sets and theoretical analysis show the proposed method can obtain promising results and outperforms some other methods. © Springer Nature Singapore Pte Ltd. 2016.

关键词： Radar imaging

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An Explainable Convolutional Neural Networks for Automatic Segmentation of the Left Ventricle in Cardiac MRI 11

An Explainable Convolutional Neural Networks for Automatic S...

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11th international conference on Electronics, Communications and Networks, CECNet 2021

作者： Liu, Jun Deng, Feng Yuan, Geng Lin, Xue Song, Houbing Wang, Yanzhi Robotics Institute School of Computer Science Carnegie Mellon University PittsburghPA United States Beijing Key Laboratory of High Dynamic Navigation Technology Beijing Information Science and Technology University Beijing China Department of Electrical and Computer Engineering College of Engineering Northeastern University BostonMA United States Embry-Riddle Aeronautical University Daytona BeachFL United States

ISBN: (纸本)9781643682402

Recently, the study on model interpretability has become a hot topic in deep learning research area. Especially in the field of medical imaging, the requirements for safety are extremely high;Moreover, it is very important for the model to be able to explain. However, the existing solutions for left ventricular segmentation by convolutional neural networks are black boxes;explainable CNNs remains a challenge;explainable deep learning models has always been a task often overlooked in the entire data science lifecycle by data scientists or deep learning engineers. Because of very limited medical imaging data, most solutions currently use transfer learning methods to transfer the model which used on large-scale benchmark data sets (such as ImageNet) to fine tune medical imaging models. Consequently, a large amount of useless parameters are generated, resulting in further barrier for the model to provide a convincing explanation. this paper presents a novel method to automatically segment the Left Ventricle in Cardiac MRI by explainable convolutional neural networks with optimized size and parameters by our enhanced Deep learning GPU Training System. It is very suitable for deployment on mobile devices. We simplify deep learning tasks on DIGITS systems, monitoring performance, and displaying the heat map of each layer of the network with advanced visualizations in real time. Our experiment results demonstrated that the proposed method is feasible and efficient. © 2022 the authors and IOS Press.

关键词： Image segmentation

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Multi-label Classification of Short Text Based on Similarity Graph and Restart Random Walk Model 11th

Multi-label Classification of Short Text Based on Similarity...

引用

11th IFIP TC 12 international conference on intelligent Information Processing, IIP 2020

作者： Li, Xiaohong Yang, Fanyi Ma, Yuyin Ma, Huifang College of Computer Science and Engineering Northwest Normal University Lanzhou China

ISBN: (纸本)9783030469306

A multi-label classification method of short text based on similarity graph and restart random walk model is proposed. Firstly, the similarity graph is created by using data and labels as the node, and the weights on the edges are calculated through an external knowledge, so the initial matching degree of between the sample and the label set is obtained. After that, we build a label dependency graph with labels as vertices, and using the previous matching degree as the initial prediction value to calculate the relationship between the sample and each node until the probability distribution becomes stable. Finally, the obtained relationship vector is the label probability distribution vector of the sample predicted by the method in this paper. Experimental results show that we provides a more efficient and reliable multi-label short-text classification algorithm. © 2020, IFIP international Federation for Information Processing.

关键词： Classification (of information)

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Machine learning Enhanced CPU-GPU Simulation Platform for 5G System 1

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11th European-Alliance-for-Innovation (EAI) international conference on Mobile Networks and Management (MONAMI)

作者： Ouyang, Yuling Yin, Caiyuan Zhou, Ting Jin, Yan Chinese Acad Sci Shanghai Adv Res Inst Shanghai Peoples R China Shanghai Frontier Innovat Res Inst Shanghai Peoples R China Shanghai Inst Technol Coll Sci Shanghai Peoples R China Chinese Acad Sci Shanghai Inst Microsyst & Informat Technol Key Lab Wireless Sensor Network & Commun Shanghai Peoples R China

ISBN: (数字)9783030947637

ISBN: (纸本)9783030947637;9783030947620

the exponential growth of mobile terminals and the explosion of data volume are promoting the continuous evolution of mobile communication network and also increasing the complexity of the system. Meanwhile, 5G system-level simulation also requires more complex operations and more data processing. Conventional system simulation platform based on CPU can not satisfy the computing power requirement of system-level simulation of 5G. For tremendously shorten the execution time, we proposed to develop the CPU-GPU based parallelization platform, which adopts Logistic Regression algorithm to optimizing the use of computational resources. Numerical results demonstrate the effectiveness in terms of reducing execution time and guaranteeing reliability of system-level simulation result in 5G scenarios.

关键词： CPU GPU System-level simulation Logistic regression enhanced Mobile Broadband (eMBB)

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Content Orientation in Integrated Product Modeling

Content Orientation in Integrated Product Modeling

引用

IEEE international conference on intelligent engineering Systems (INES)

作者： Laszlo Horvath Imre J. Rudas Gerhard P. Hancke John von Neumann Faculty of Informatics Budapest Technology Institute of Intelligent Engineering Systems Budapest Hungary Department of Electrical Electronic and Computer Engineering University of Pretoria Pretoria South Africa

Changes in engineering for development of product in the direction of increased complexity, more variants, and customer demand orientation stimulates implementation of advanced information technology in the form of virtual space. For this reason, concept of integrated product model has been implemented in comprehensive descriptions for lifecycle management of product information. Communication between engineer and modeling procedure is a critical factor. the authors identified data orientation of the recent integrated product modeling as a barrier for more efficient communication on user interfaces of product modeling systems. As a possible contribution to development of solution for this problem in industrial professional modeling systems, they propose content oriented layers between human and data oriented models in this paper. Following this, integration issues in content oriented product model are discussed. Next, relevant functions and modeling techniques for the handling of modeled object information are introduced and evaluated. Finally, a method is shown for the propagation of changes initiated for modeled objects in their affect zones.

关键词： Humans ISO standards Information technology User interfaces Computer aided manufacturing CADCAM Automation Standards development intelligent systems Systems engineering and theory

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Educational inclusion: Teachers’ technical needs and supports 11th

Educational inclusion: Teachers’ technical needs and suppor...

引用

11th international conference on EUropean Transnational Education, ICEUTE 2020

作者： Núñez, Beatriz F. Valenti, Antonella Sapia, Sonia Universidad de Burgos C/Villadiego 1 Burgos09001 Spain Universitá della Calabria Via Pietro Bucci 7/11/B Aravaca di Rende Italy

ISBN: (纸本)9783030577988

the Erasmus + Project "European diversity design for inclusive education" (EURODDIP-e), co-financed by the European Union, aims to provide education professionals with the knowledge, tools and devices necessary to assess the individual needs of the Students with difficulties in the upper limbs and personalize the Information and communication technologies (ICT) resources (interface, software, buttons, etc.). A Questionnaire Teacher (QT) with α = 0.75, has been prepared to find out the needs of professionals in the teaching-learning process, taking into account the characteristics of the students and the existing technological possibilities, both in paper format and by using Google Forms is anonymous, and collects sociodemographic data, as well as 27 other items (16 yes/no answers, 10 Likert-type answers and the last open-ended answer. 1237 teachers from public and private schools in Belgium, Italy, Portugal and Spain, have responded. Items related to the training and performance of teachers in their teaching with inclusion students and use of ICT are analyzed. the need for training and greater resources is unanimous. English, French and Spanish versions in https://***/handle/10259/5262. It is the beginning for the elaboration of a methodology for the detection of capacities for all partner countries. © the Editor(s) (if applicable) and the Author(s), under exclusive license to Springer Nature Switzerland AG 2021.

关键词： Students

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A Web Based Face Counter Prediction System from Only Fingerprints

A Web Based Face Counter Prediction System from Only Fingerp...

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international conference on Machine learning and Applications (ICMLA)

作者： Seref Sagiroglu Uraz Yavanoglu Dept. of Computer Engineering Gazi University Ankara Turkey

Up to now a large number of approaches and algorithms about biometric recognition techniques have been developed and proposed in the literature in details. Relationships about biometrics have recently been studied in the field by author research group. this paper presents a web based intelligent face mask prediction system based on artificial neural networks to predict faces from only fingerprint images. the aim of this study is to develop an online platform to be used by users, researchers or academics around the world. the results have been shown that the system can be used for live test through internet. the proposed web based system is successful to support and encourage researchers around the world to see and exercise this new concept in biometrics. the developed system predicts an appropriate face mask covering nose, eyes, ears and mouth from fingerprint images with the help of an intelligent model.

关键词： Face Fingerprint recognition Artificial neural networks Artificial intelligence Image matching Face recognition Feature extraction

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