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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571-580 订阅

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A Synoptic Survey on Personality Prediction System using MBTI 3

A Synoptic Survey on Personality Prediction System using MBT...

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

作者： Justindhas, Y. Mohanraj, Sabari Mutheeswari Shivani, R. Easwari Engineering College Department of Computer Science and Engineering Chennai India

ISBN: (数字)9781665479714

ISBN: (纸本)9781665479714

This survey paper presents a Personality Prediction System based on Meyer-Briggs-Type-Indicator (MBTI) that computes and identifies the personality traits of an individual using a qualified machine learning technique. This system helps individuals to break their curiosity about knowing themselves and it is highly used as a tool for psychological profiling. Personality prediction is influential in building an individual's confidence and helps to tone oneself for the foreseen challenges of their life. For instance, this could help people identify their interests and hidden skills. This system gives a clear overview of them and will help to guide and choose one's career path. Though there have been many personality prediction systems in the past, this system stands ahead of them by using digital questionnaire forms to process MBTI trait cards and its method of digesting the data using machine learning which is capable of handling dynamic input. To build this system, relevant literature papers were reviewed and analyzed, to build a different system but to provide the best results that could be compared and examined. © 2022 IEEE.

关键词： machine learning

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Semantic Analysis and machine learning Techniques for Enhancing Content-Based Image Retrieval 3rd

Semantic Analysis and Machine Learning Techniques for Enhanc...

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3rd international conference on Mechanical and Energy Technologies, ICMET 2023

作者： Sunil, G. Manochandar, S. Atheeq Sultan Ghori, Md. Kumar, K. Suresh Kumar, Binod Dhanke, Jyoti School of Computer Science and Artificial Intelligence SR University Telangana Warangal India Department of Master of Business Administration CARE College of Engineering Tamil Nadu #27 Dindugal Main Road Tamil Nadu Thayanur620 009 India Department of Computer Science and Engineering Telangana University Nizamabad Telangana State Nizamabad India MBA Department Panimalar Engineering College Varadarajapuram Poonamallee Chennai India JSPM Rajarshi Shahu College of Engineering Maharashtra Pune India Savitribai Phule Pune University Maharashtra Pune India

ISBN: (纸本)9789819727155

Multimedia data has grown in volume and complication due to the explosion of computing innovations and the introduction of the Internet. The client can submit a request to the content-based image retrieval (CBIR) structures, which allows it to obtain the needed photo from the image collection. This platform has been designed as an effective image-retrieving instrument. Unfortunately, there are several issues with the typical relevant response of CBIR that would reduce the platform's efficiency, including imbalances in the training collection and categorization problems, inadequate learning collection problems, and user problems with constrained data. This paper suggests using a machine learning-driven (ML) semantic analysis for CBIR with local neighbor patterns (LNP).To increase the efficacy of this platform, this study employed 3 different kinds of datasets: texture, hue, and face datasets. This study employed the LNP approach in conjunction with ML methods to boost the accuracy of this platform. The performance evaluation demonstrates that the application of ML methods in conjunction with regional patterns enhances the mean accuracy from 36.2 to 85.6% when using LNP with cubic the Support Vector machine (SVM), from 82.5 to 99.5% when using LNP with acceptable kernel neural network (KNN), and from 56.6 to 95% when using LNP with ensemble subdomains discriminatory. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Support vector machines

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DDoS Attack Detection Using machine learning 3rd

DDoS Attack Detection Using Machine Learning

引用

3rd international conference on Information Technology, InCITe 2023

作者： Swati, Jadhav Nitin, Pise Singh, Shruti Sinha, Akash Sirvi, Vishal Srivastava, Shreyansh Computer Engineering and Technology MIT World Peace University Pune India Department of Computer Engineering Vishwakarma Institute of Technology Pune India

ISBN: (纸本)9789819959969

Distributed denial of service attack, sometimes termed as the ddos attack, is now the most dangerous cyber threat. This is primarily accomplished through network traffic bombardment, in which attackers attempt to generate a huge number of fake IP address requests, which can affect the server’s ability to provide services to legitimate requests, and which can affect server resources, such as bandwidth speed, buffer size, fiber optic cable transmission rate which are slowed down. This work proposes application of MLmodels for distributed denial-of-service assaults. To detect assaults and typical circumstances, machine learning methods such as K-Nearest Neighbour, Decision Tree, Logistic Regression, Naive Bayes, and Quadratic Discriminant Analysis are utilized. The Mininet’s auto generated dataset is used for experimental purposes. In this study, the Google colab platform was employed for implementation, and the findings were analysed and compared. The Decision Tree Classifier, which has an accuracy of 96.513867%, is the best performing model. Other machine learning techniques employed in denial of service attacks are compared to previous work. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Decision trees

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Utilizing machine learning to Develop an Improved Real-Time Data Analysis System 3

Utilizing Machine Learning to Develop an Improved Real-Time ...

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3rd international conference on Smart Generation Computing, Communication and Networking, SMART GENCON 2023

作者： Khandari, Harsimrat Sahoo, Girija Shankar Raja Praveen, K.N. Shree, Ritu Umamaheswari, B. Yashwant, V. Chitkara University Institute of Engineering and Technology Chitkara University Centre of Interdisciplinary Research in Business and Technology Punjab India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh India Faculty of Engineering and Technology Department of Computer Science and Engineering Karnataka Bangalore India Vivekananda Global University Department of Computer Science & Application Jaipur India Prince Shri Venkateshwara Padmavathy Engineering College Department of Computer Science and Engineering Chennai India Vishwakarma Institute of Information Technology Department of Computer Engineering Pune India

ISBN: (纸本)9798350319125

With the constantly growing volume of facts being produced, conventional data evaluation structures are regularly insufficient in terms of presenting an correct overview of the most modern-day data. The utilization of system mastering provides the potential to create an improved real-time records evaluation device this is more able to making experience of and knowledge the records. The development of an progressed actual-time statistics evaluation device utilizing system studying can hugely enhance statistics analysis techniques by means of integrating relevant data and structured analyses of the identical. this will include strategies inclusive of natural language processing and clustering algorithms to perceive trends, sentiment evaluation to understand customer feedback, and predictive analytics to better perceive areas for improvement. Moreover, the realtime statistics analysis system can be further enhanced by means of incorporating AI to make extra correct predictions, as well as reinforcement studying to evolve present models as new statistics is integrated. this would allow the system to learn more efficaciously and modify its algorithms to continually enhance its overall performance. Universal, by using machine studying to develop an advanced actual-time statistics evaluation system, extra correct and comprehensive insights can be generated from information, and groups can use this facts to better tell their choice making. moreover, temporal records evaluation can be advanced with faster response times as a result of the device being able to process records © 2023 IEEE.

关键词： Statistics

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Design and application of English Assisted learning System Based on Mobile learning Platform 3

Design and Application of English Assisted Learning System B...

引用

3rd international conference on machine learning and Big Data Analytics for IoT Security and Privacy, SPIoT2023

作者： Huang, Xiaojing Public Course Department Hainan Vocational University of Science and Technology Haikou571126 China

For the purpose of developing a new kind of auxiliary learning method or tool, the author puts forward a kind of personalized mobile EFL learning system based on Android and vocabulary learning. The system consists of Remote Management Server, Client Mobile learning System and Data Synchronization Intelligence Agent. This system has carried on the corresponding design in view of the different student, the different new word level, the different study, the different memory stage. The study found that there were 15 multiple choice questions before and after the exam, and 15 closed questions, with a full score of 30. In order to ensure accurate testing, the difficulty levels of both tests are controlled within a similar range. Although learners' academic performance in multiple choice questions did not significantly improve, their vocabulary ability in cloze tests significantly improved. It has been proven that the proposed system can effectively improve English learning performance, and the simulation also verifies the effectiveness and practicality of the system. © 2023 The Authors. Published by Elsevier B.V.

关键词： learning systems

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application of Deep learning in Monitoring and Warning of Network Public Opinion in Universities 3

Application of Deep Learning in Monitoring and Warning of Ne...

引用

3rd international conference on computer Science and Management Technology, ICCSMT 2022

作者： Li, Menggang Wuhan University of Science and Technology Hubei Province Wuhan China

ISBN: (纸本)9798350320404

This paper uses the deep learning technology of convolutional neural network (CNN) and Word2vec to improve the accuracy of network public opinion monitoring in universities. This paper uses crawler technology to obtain data from Sina Weibo, Zhihu, Baidu Tieba and other websites, preprocesses hot topics related to public opinion in colleges and universities, uses Word2vec model to generate word vectors, uses CNN to extract features and classify emotional tendencies, and establishes a more effective monitoring and early warning system of public opinion in colleges and universities. This study has good theoretical value and practical significance to further strengthen the work of news and public opinion in Colleges and universities, and to enhance the ability of governance and the modernization level of governance system in Colleges and universities. © 2022 IEEE.

关键词： Convolutional neural networks

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machine learning Approach Based Phishing Email Text Analysis (ML-PE-TA) 3

Machine Learning Approach Based Phishing Email Text Analysis...

引用

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

作者： Ahammad, Shaik Mulinti Mustaq Raviteja, Tangudu Koushik, Jami Dinesh, Pamidi Venkata Ashok, Asha Amrita Vishwa Vidyapeetham Department of Computer Science and Engineering Amritapuri India

ISBN: (数字)9781665410052

ISBN: (纸本)9781665410052

Phishing based incidents are the procedure of posting illegal or dishonest communications that seems to be originated from a trustworthy sending node. It is commonly reflected in the case of email transmission. The aim is to rob one's important personal information which includes credit/ debit card details, login information, account related data etc. In one way or another, Phishing emails are can trick users into revealing crucial technical or personal information. Users needs to be very careful and cautious when working with the emails they receive in their Inbox. In addition to verifying sender information, users must be wise enough in analyzing the body of the email to remain protected against such frauds. To account for this reason, this study have proposed a simple yet effective approach, ML-PE-TA,for analyzing the email text body with machine learning algorithms. Using the proposed approach, this paper could achieve an accuracy of 96 percentage with a minimum count of vital features only for Phishing Email Text Analysis. At the same time, by the application of dimensionality reduction techniques, the proposed approach is able to reduce the dimensionality of the data considerably, which is better than state-of-the-art existing phishing email detection techniques which have much greater number of features and lesser accuracy rate. © 2022 IEEE.

关键词： Electronic mail

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Design and Implementation of Virtual Character based on Facial Motion Capture 3

Design and Implementation of Virtual Character based on Faci...

引用

2022 3rd international conference on computer Information and Big Data applications, CIBDA 2022

作者： Qi, Jiangyuan Wang, Shanshan School of Art and Design Changjiang Polytechnic China School of Computer Technology and Software Engineering Wuhan Polytechnic China

ISBN: (纸本)9783800758760

The metaverse is one of the hottest concepts right now. With the development of computer technology, digital virtual human gradually developed from concept to practical application. At present, virtual characters have gradually been launched on major video platforms. This paper introduces a virtual character implementation scheme based on facial motion capture technology. This article contains the entire process from 3D modeling, to model animation rigging, and facial motion capture, and finally applying the captured facial motion to model animation. In this paper, the Unity3d engine mainly implements the rendering of models and animations, while facial motion capture uses deep learning-based algorithms. Through the design and implementation of the entire system, it provides a set of solutions for AI engineers. © VDE VERLAG GMBH - Berlin - Offenbach.

关键词： 3D modeling

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Multifold Secured Bank application Authentication Service Using Random Visual Cryptography and Multimodal Steganography with Blockchain Technology 1

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3rd international conference on Recent Trends in machine learning, IoT, Smart Cities and applications, ICMISC 2022

作者： Jahnavi, S. Nandini, C. Computer Science and Engineering Department Dayananda Sagar Academy of Technology and Management Visvesvaraya Technological University Karnataka Bangalore560082 India

ISBN: (数字)9789811960888

ISBN: (纸本)9789811960871

DATA protection is becoming increasingly critical as the demand for online services grows, which biometrics authentication can help with. To communicate biometric data authenticating services over the Internet in a secure channel is essential. To ensure the security and the existence of the biometric information over the communication channel Random Visual Cryptography and Multimodal Mask Steganography is used. The biometric features captured are embedded using multimodal mask steganography, considering mask image and cover image. The resultant stego image shares are created using Random visual cryptography technique. The resultant shares are placed in blockchain using blockchain technology to improve security aspects of the cloud application and reliable transmission of data. Combining proposed Random Visual cryptography and multimodal mask steganography methods with blockchain technology ensures high reliable authentication system of server room access or banking application. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Authentication

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machine learning Models based Mental Health Detection 3

Machine Learning Models based Mental Health Detection

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

作者： Karunakaran, Manivannan Balusamy, Jeevanantham Selvaraj, Krishnakumar Psna College of Engineering and Technology Department of Computer Science and Engineering Tamil Nadu India Jainee College of Engineering and Technology Department of Computer Science and Engineering Tamil Nadu India Theni Kammavar Sangam College of Technology Department of Electronics and Communication Engineering Tamil Nadu India

ISBN: (数字)9781665410052

ISBN: (纸本)9781665410052

This century will be the fastest ever, putting a heavy burden on future generations, especially students. Future generations will face enormous stress, competition, social issues, and constant pressure. Their lives will become a race. That leaves students with mental health issues that lead to disorders. Five of the most common types of disorders that young people especially face are bipolar disorder (mood disorders), anxiety disorders, depression, eating disorders, and sleep issues. As machine learning plays a vital role in the easiness of human life, this paper also uses machine learning (ML) algorithms to screen Mental Health by using a Mental Disorder Questionnaire (MDQ). In this research, there are two types of Questionnaires employed. The first Self Reporting Questionnaire-15 (SRQ-15) has 15 general mental disorder questions with the option of Yes/No. The second Self Reporting Questionnaire-25 (SRQ-25) has 25 questions, five questions for each of the five different mental health disorders mentioned. Within each section, the user fills the questionnaire according to the instructions. We labeled the train data set using Supervised machine learning. So we use different algorithms to compare results with manual testing. © 2022 IEEE.

关键词： Surveys

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