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检索条件"任意字段=3rd International Conference on Machine Learning and Computer Application, ICMLCA 2022"

共 1897 条记录，以下是661-670 订阅

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Research on Prediction Method of Objective Assessment of Building Acoustics Based on machine learning 3

Research on Prediction Method of Objective Assessment of Bui...

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2023 3rd international conference on Electrical, Electronics, and Computing Technology, EECT 2023

作者： Wan, Yupeng Zhou, Yuanbo Wen, Jie Chen, Zheng Zhao, Jing Institute of Acoustics National Institute of Measurement and Testing Technology Chengdu China Sichuan Haiyan Acoustic Technology Co. Ltd Chengdu China

The purpose of this study is to predict the objective assessment of building acoustics more accurately and efficiently. In this paper, the neural network technology based on machine learning and computer acoustic simulation technology are combined to extract 10 typical characteristic parameters and 3 target parameters of 800 halls and rooms. Three matrix training sample databases are established by using Odeon platform. The reverberation time and speech transmission index are trained by BP neural network data fitting. The R results of the target parameters in this study are all more than 0.95. The MSE of the reverberation time parameter is in the range of 0.01-0.05 and the MSE of the STI parameter is less than 1 × 10-4. The results show that the neural network has good prediction accuracy, data generalization and application applicability. This prediction method can quickly evaluate the target parameters, reduce manpower and material resources, and improve work efficiency. © Published under licence by IOP Publishing Ltd.

关键词： Speech intelligibility

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Colombian Sign Language Classification Based on Hands Pose and machine learning Techniques 3rd

Colombian Sign Language Classification Based on Hands Pose a...

引用

3rd international conference on Smart Technologies, Systems and applications, SmartTech-IC 2022

作者： Vera, Anny Pérez, Camilo Sánchez, Juan José Orjuela-Cañón, Alvaro D. School of Medicine and Health Sciences Universidad del Rosario D.C. Bogotá Colombia Escuela Colombiana de Ingeniería Julio Garavito D.C. Bogotá Colombia

ISBN: (纸本)9783031322129

New technologies can improve the inclusion of deaf (and hearing loss) people in different scenarios. In the present work, a classification of the Colombian sign language alphabet was implemented. For this, the employment of the media-pipe hands pose tool was used to feature extraction process. Then, three machine learning models: support vector classifiers, artificial neural networks and random forest, were trained to determine the best proposal. Results show how a neural network with one hidden layer obtained the best performance with 99.41%. The support vector classifier reached an accuracy of 99.12%, and the worse result was achieved by the random forest model with 96.67% in the classification. The proposal can contribute with advances in the sign language recognition in the Colombian context, which has been worked in different approaches with more complex models to do similar classifications. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： machine learning

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Faster R-CNN and YOLOv3: A general analysis between popular object detection networks 3

Faster R-CNN and YOLOv3: A general analysis between popular ...

引用

3rd international conference on Signal Processing and machine learning, CONF-SPML 2023

作者： Dong, Wenbo Computer Science University of Science and Technology of China Anhui Hefei230026 China

computer vision is developing really fast in recent years, and object detection is now one of the hottest topics. faster region-based convolutional neural network (faster R-CNN) and You Only Look Once (YOLOv3) are two popular modules to solve object detection problems, but they are implemented in different ways and thus have different performance in practice. This article is going to introduce these two modern modules and make a few experiments to compare the performance of each module with various datasets. This analysis will focus on speed, accuracy and the performances in different situations. Two specific studies will be mentioned as two typical examples of object detection application: face mask detection and greenhouse detection from satellite images. At last, the article will draw out a conclusion, make some suggestions for the choice of faster R-CNN and YOLOv3 and make a prospect for the future. It turns out that generally faster R-CNN fits tasks that require high accuracy better and YOLOv3 can realize real-time detection tasks. © Published under licence by IOP Publishing Ltd.

关键词： Object detection

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Prediction of DDoS Flooding Attack using machine learning Models 3

Prediction of DDoS Flooding Attack using Machine Learning Mo...

引用

3rd international conference on Smart Technologies in Computing, Electrical and Electronics, ICSTCEE 2022

作者： Patil, Pooja S Deshpande, S.L. Hukkeri, Geeta S Goudar, R.H. Siddarkar, Poonam Visvesvaraya Technological University Department of Computer Network Engineering Belagavi India

ISBN: (纸本)9781665456647

Nowadays multifarious types of Distributed Denial of Services attacks occur owing to the rapid growth in technology and also potentially cause harm in Software Defined Network architecture. As a consequence, it is found one among the crucial and commonly occurring cyber-Attack. There are many traditional and advanced methods for detecting these attacks. This paper intends to build a machine learning based model for predicting the DDoS Flooding attacks. The DDoS flooding attacks to be anticipated are involved with numerous types. The ML models used to classify these attacks are namely, Logistic Regression, K-nearest neighbour, Multi-Layer Perceptron, and, Decision Tree classifiers. The implementation is been done with a jupyter notebook with required python packages installed. Among these four classifiers, KNN and Decision Tree Classifiers have shown almost similar and best accuracy of 99.98 percent in TCP and ICMP flooding attack prediction. The Decision Tree Classifier has shown the best accuracy of 77.23 percent compared to others in UDP flooding attack prediction. © 2022 IEEE.

关键词： Denial-of-service attack

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Research on Software Defect Prediction and Analysis Based on machine learning 3

Research on Software Defect Prediction and Analysis Based on...

引用

3rd international conference on Modeling, Simulation, Optimization and Algorithm, ICMSOA 2021

作者： Peng, Xuemei School of Computer and Information Engineering Nanchang Institute of Technology Jiangxi Nanchang330044 China

The defects of machine learning prediction technology can be more comprehensive and automatic learning model to find the defects in software has become the main method of defect prediction, selection and study of algorithm is the key to improve the accuracy and efficiency of machine learning. Comparing different machine learning defect prediction methods reveals that the algorithms have different advantages in different evaluation indicators, the use of these advantages and combining the stacking ensemble learning method in machine learning is put forward different prediction algorithm of prediction results. As software metrics and again the prediction model of software defect prediction combined machine learning algorithm is based on the experiment with the model of Eclipse, the data sets show the effectiveness of the model. © Published under licence by IOP Publishing Ltd.

关键词： Forecasting

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application of Intelligent Flipped Classroom Technology and HCI Interactive Mode in English Online Course Design from Smart Data Mining Perspectives 3

Application of Intelligent Flipped Classroom Technology and ...

引用

3rd international conference on Electronics and Sustainable Communication Systems, ICESC 2022

作者： Tao, Jie Wei, Wengming Nanning University No.8 Longting Road Guangxi Nanning City530200 China

ISBN: (数字)9781665479714

ISBN: (纸本)9781665479714

In order to make students more flexible and active, the mobile Internet has spawned a "flipped classroom"teaching mode and human-computer interaction mode that subverts the traditional teaching mode. This article will start with the connotation of flipped classroom and data mining technology, and explore its application methods. In the current SPOC flipped classroom teaching mode, the data mining of learning progress is carried out, combined with a certain human-computer interaction, starting from the theoretical basis, teaching objectives, implementation conditions, operating procedures, and teaching evaluation, which is a relatively complete and systematic teaching mode. The flipped classroom teaching mode based on SPOC is designed. © 2022 IEEE.

关键词： Data mining

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machine learning Based Impostor Detection by Invariant Features from Nir Finger Vein Imaging 3

Machine Learning Based Impostor Detection by Invariant Featu...

引用

3rd international conference on Innovations in computer Science and Software Engineering, ICONICS 2022

作者： Rasool, Akhtar Rehman, Faisal Sarfaraz, Nadeem Sharif, Hanan Khan, Rashid Khan, Abdul Manan Lahore Leads University Department of Computer Science and Information Technology Lahore Pakistan

ISBN: (纸本)9781665461412

Biometrics mostly used as personal identification accordingly securing a client against the unapproved utilization of his or her identity. Acquiring biometric information is getting to be simpler. Smartphones and other advanced technologies exist from which biometric data can collect easily without the knowledge of others. Finger vein authentication is a method for biometric verification that depends on a vein pattern, which is located beneath the human finger's skin. Veins are covered with skin that cannot be copied by others. In this research, our focus is on these invariant features of finger veins. We have collected invariant features from various recent features extraction techniques and then classified with state-of-The-Art machine learning classifiers. For this purpose, we have used publicly available finger vein image databases. The performance has been evaluated by various evaluation metrics and comparative analysis of various machine learning classifiers has been presented to describe the performance of these classifiers on the said data set. © 2022 IEEE.

关键词： Biometrics

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AI Enabled Educational Bot to Improve learning Outcomes using Bag of Words Algorithm 3

AI Enabled Educational Bot to Improve Learning Outcomes usin...

引用

3rd international conference on Intelligent Computing, Instrumentation and Control Technologies, ICICICT 2022

作者： Sankar, S. Raj, Adithya Pothan Ramyaa, S. Pavithra, S. Kcg College of Technology Department of Computer Science and Engineering Chennai India

ISBN: (数字)9781665410052

ISBN: (纸本)9781665410052

Educational institutes across India have closed due to COVID-19 pandemic which has jeopardized academic schedules. To maintain their academic activities, several Indian educational institutes have shifted to online learning platforms. However, there are still questions about the effectiveness, design, and readiness of e-learning. In light of this fact, E-learning still tends to be controversial. As a result, it is inevitable to design an application with greater usability. In this paper, a novel application tool is developed and the design is proposed to enhance student knowledge and facilitate their study process, so they can study in comfort at home. The proposed system allows students to receive personalized educational assistance and also allows the students to get instant responses to all their questions throughout the day via a voice-enabled chatbot. It facilitates the connection between students and tutors, as well as the awarding of mind coins and badges based on how well they do, motivating them to learn more. Data analytics is incorporated and usability is measured. The result shows that the proposed system has greater usability resulting in a progressive improvement in the student's performance. © 2022 IEEE.

关键词： E-learning

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application of artificial intelligence image recognition technology in power system 3

Application of artificial intelligence image recognition tec...

引用

3rd international conference on Artificial Intelligence and Electromechanical Automation, AIEA 2022

作者： Du, Xiaoyue Gu, Guangheng Yang, Fan Yunnan Power Grid Materials Co. Ltd. Kunming650220 China

ISBN: (纸本)9781510657281

Under the vigorous promotion of global energy Internet, China's AC/DC power grid construction has been developed rapidly and both artificial intelligence technology and machine learning technology have been developed by leaps and bounds. computer-based image pattern recognition technology is an important part of computer application technology. With the rapid development of digital image processing technology and pattern recognition technology, image pattern recognition technology has been more comprehensively applied in various aspects such as industry, agriculture, national defense, scientific research and medicine. In this paper, we introduce the image detection technology and image detection algorithm for substation inspection robots and acquire image data files through image acquisition terminal sensors to realize the categorization of feature amount. So as to realize the annotation of pre-set features based on the training model. An optimized classifier and optimized image features are used to build an efficient and accurate image classification model. Artificial intelligence image recognition technology for power equipment image recognition is important to further improve the automation and intelligence level of substations. © 2022 SPIE.

关键词： Image recognition

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application Development for a Project using Flutter 3

Application Development for a Project using Flutter

引用

3rd international conference on Smart Electronics and Communication, ICOSEC 2022

作者： Nagaraj, K. Prabakaran, B. Ramkumar, M.O. Computer Science Engineering Ifet College of Engineering Gangrampalayam Villupuram India

ISBN: (数字)9781665497640

ISBN: (纸本)9781665497640

Plant disease detection consumes more time and money for farmers and also manual detection errors may also lead to low crop cultivation rate. The proposed study has used the YOLO V3 demonstration with a transfer learning approach to identify the infections in photos of betel leaves. To significantly increase betel leaf cultivation, the diseases should be identified at an early stage before it spreads to the entire field. The proposed betel leaf disease detection strategy accomplishes a proper balance of exactness and recognition speed. The parameters of the suggested demonstration were adjusted for the classification task, and a high level of precision of around 95.6% was attained. © 2022 IEEE.

关键词： Object oriented programming

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