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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381-390 订阅

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Deep Transfer learning for IoT Intrusion Detection 3

Deep Transfer Learning for IoT Intrusion Detection

引用

3rd international conference on Computing, Networks and Internet of Things, CNIOT 2022

作者： Xue, Bing Zhao, Hai Yao, Wei Northeastern University College of Computer Science and Engineering Shenyang China

ISBN: (纸本)9781665469104

Intrusion detection system (IDS) is crucial to security architecture of Internet of Things (IoT). In recent researches, the traditional machine learning and deep learning methods have been applied to the field of intrusion detection and achieved satisfactory performance. However, due to diverse IoT and dynamic network environment, it is difficult to use a single model for heterogeneous IoT networks and collect enough labeled data to train the new model. To solve these issues, we propose an intrusion detection approach based on heterogeneous transfer learning (HTL) for building an intrusion detection model with strong adaptability. Specifically, the approach consists of an Autoencoder architecture for aligning the heterogeneous features and lightweight Convolutional Neural Network (CNN) for unsupervised domain adaptation. Extensive experimental results on three public datasets reveal that the effectiveness of our proposed approach in the IoT environment with unlabeled and limited data. © 2022 IEEE.

关键词： Internet of things

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Vibrations Signal Analysis of Cantilever Beam Using machine learning 3rd

Vibrations Signal Analysis of Cantilever Beam Using Machine ...

引用

3rd international conference on Communication, Networks and Computing, CNC 2022

作者： Sharma, Lali Sharma, Jai Kumar Khatri, Pallavi ITM University Gwalior India

ISBN: (纸本)9783031431449

Vibrations are common phenomena seen in mechanical structures that can be detrimental to many systems. If not monitored, they can cause damage to structures, Vibrometer is sensor used for measuring vibrations of mechanical structures, machines, as well as sound level in an area and will collect lot of data that is to be analyzed to determine the strength of the structures. machine learning is the basic working technology for prediction and determining the work proposes system aims to predict the health of a structure, converting the cantilever beam vibration reading to graph which is able to give the correct state or health of the structure. This work will cover all the major challenges faced due to natural down fall of quality of structure. The aims to able to check the Structural Health and able predict the condition of the structure. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： machine learning

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Spam and Non-Spam URL Detection using machine learning Approach 3

Spam and Non-Spam URL Detection using Machine Learning Appro...

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3rd international conference for Emerging Technology, INCET 2022

作者： Raj, Ritu Singh Kang, Sandeep University Institute of Engineering Computer Science & Engineering Chandigarh University Mohali India

ISBN: (纸本)9781665494991

In the modern world, where everyone is connected with internet, a threat has always surrounded every internet user which steals user credentials by various means;this threat is known as Phishing. The attacker acts as a trustworthy agent and steals victim's credentials or personal details. This information is then used for illegal purpose which may result in identity theft or financial loss. This project provides a better understanding on how phishing attacks are carried out by attackers and how these attacks are detected by websites that uses various detection methods. A tool is designed using machine learning and deep neural net which classify Uniform Resource Locator (URLs) as phishing or legitimate URL. Dataset is collected from various resources that contain phishing and legitimate URLs of websites and then these datasets are provided to the neural net for supervised training. Various classification algorithms are, then, applied on these datasets and then accuracy of these algorithms is predicted. © 2022 IEEE.

关键词： Websites

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Influence of Deepfake Terminology on Content-Emerging Threat Reduction 3

Influence of Deepfake Terminology on Content-Emerging Threat...

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3rd international conference on Innovative Sustainable Computational Technologies, CISCT 2023

作者： Tripathi, Rajeev Mishra, Vinay Kumar Kumar, Vivek Sengar, Alok Singh Pandey, Neeraj Kumar Mishra, Amit Kumar School of Management Sciences Department of CAS Lucknow India Babu Banarasi das University Department of Computer Application Lucknow India Teerthanker Mahaveer University Department of CSE Moradabad India IIMT University Department of CSE Meerut India School of Computing IIMT University Dehradun India Graphic Era Hill University Department of CSE Dehradun India

ISBN: (纸本)9798350303360

A significant development in the rapidly expanding fields of Deep and machine learning resulted in architectures that can create convincing synthetic content sometimes known as deepfakes. The danger arises when doctored photographs, films, and audios blur the distinction between fake and real content and are employed as weapons to inflict new levels of damage. This work analyzes the effectiveness of Big Data processing on operational parameters and focuses on data-dimensionality factors. It resolves big-data complications using DL and ML for decision-making mechanisms in the enterprise sectors and corporate sectors using in-depth analysis. © 2023 IEEE.

关键词： Deep neural networks

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Applicability of Heavily Compressed JPEG Tampered Images in Social Media and Supervised machine learning towards Detection of Forgery 3

Applicability of Heavily Compressed JPEG Tampered Images in ...

引用

3rd international conference on Advancement in Electrical and Electronic Engineering, ICAEEE 2024

作者： Sarkar, Saswata Roy, Sourav Dey Das, Santanu Saha, Priya Bhowmik, Mrinal Kanti 799022 India Agartala799006 India

ISBN: (纸本)9798350388282

The evolution and progress of mobile devices and social networks have made it a simple task for inexperienced users to acquire photos and share them on social platforms. Due to the availability of media editing softwares, forgers can efficiently spread rumors thereby creating forged images/ videos (i.e., manipulated/ tampered content) which may create negative sentiments among the people of the country. Thus, the availability of highly sophisticated systems/ techniques for finding tampered traces in images and videos has received significant attention. With the availability of the conventional methods for forgery detection, the detection of the forgery in all the categories of images is not possible especially when the manipulated images are heavily compressed. This paper highlights and analyses the challenges of conventional forensic methods for forgery localization in heavily compressed tampered images. To meet the specific necessities and challenges of forgery localization in images, in this paper we investigated the encoder-decoder based deep learning frameworks (i.e., SegNet and U-Net) for segmentation of the forged regions from the holistic tampered images. Also, we have investigated the perception capabilities of the backbone CNN architectures on the encoder-decoder frameworks for precise segmentation of the forged regions from the images. Experiments have been conducted on publicly available datasets including CASIA-V2 and CMFD datasets and our own designed dataset. Experimental results demonstrate that SegNet+MobileNet on CASIA-V2 dataset, U-Net+AlexNet on CMFD dataset, and SegNet+ResNet-101 have been observed to precisely extract the forged portions from the entire altered images with F1-Score of 0.58, 0.57, and 0.49 respectively. © 2024 IEEE.

关键词： Deep learning

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Research on the innovation and application of big data in higher education 3

Research on the innovation and application of big data in hi...

引用

3rd international conference on Intelligent Computing and Human-computer Interaction, ICHCI 2022

作者： Liu, Wenhua Office of Planning Management and Quality Assessment Shanghai Urban Construction Vocational College Shanghai China

ISBN: (纸本)9781510661301

The appearance of big data provides many changes to our daily lives. Among these changes, the innovation and application of big data in higher education are greatly remarkable. Therefore, the paper firstly analyzes the background of big data appearance. Then the paper describes the main application in higher education, which includes improving college planning, promoting college development, obtaining the teaching reality, enhancing teaching efficiency, optimizing learning experience, improving learning quality and boosting science research. After that, the paper provides two technologies of big data analysis: educational data mining and learning analysis. The applications of the two technologies in higher education mainly include classification, forecast, clustering, outlier detection and others. At the same while, the paper also describes the challenges of big data application in higher education, which are epistemology, methodology, technology, law, ethic and other dilemma. © 2023 SPIE.

关键词： Data mining

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Analysis Of machine learning Algorithm for Prognostication of Parkinson's Disease Using Speech Articulation 3

Analysis Of Machine Learning Algorithm for Prognostication o...

引用

3rd international conference for Emerging Technology, INCET 2022

作者： Fathima, G Babu, Tharunaa Shoban Srimaan, A Shubhakar, B C Adhiyamaan College of Engineering Department of Computer Science and Engineering Hosur India

ISBN: (纸本)9781665494991

The disease named Parkinson's is a popular health disease among humans that is progressively increasing day by day and has had its effects on many countries. Thus, it is very important to diagnose the disease at the starting stage which has been a challenging action for the researchers, as the symptoms to diagnose the disease differ from person to person and it can exist in people from mid age to older age. In this paper the performance of different models such as adaboost classifier, logistic regression, support vector classifier and decision tree classifier has been evaluated using various metrics i.e. accuracy, precision, specificity. It primarily focuses on the symptoms of speech articulation problems in persons that are being diagnosed with Parkinson's and develops the model using Support Vector machine. To forecast the diagnosis of Parkinson's, the Boruta feature choosing technique is utilised for the determination of the most essential features comparing to all the other features. © 2022 IEEE.

关键词： Support vector machines

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Analyzing the Benefits of Applying machine learning to Real-Time Data Analysis 3

Analyzing the Benefits of Applying Machine Learning to Real-...

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

作者： Yadav, Rakesh Kumar Mahesh, T.R. Kumar, Ajay Jayadurga, R. Vishal, A. Sood, Gourav 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 Department of Computer Science & Engineering Vivekananda Global University Jaipur India Prince Shri Venkateshwara Padmavathy Engineering College Department of Master of Business Administration Chennai127 India Department of Computer Engineering Vishwakarma Institute of Information Technology Pune India Centre of Interdisciplinary Research in Business and Technology Chitkara University Institute of Engineering and Technology Chitkara University Punjab India

ISBN: (纸本)9798350319125

The application of device learning to actual-time data analysis has the potential to revolutionize the way businesses make decisions. With the capacity to procedure big volumes of data fast and correctly, system learning can provide insights that tell strategic decisions at the same time as promoting information-pushed choice making. This evaluation can assist agencies increase efficiency, lower expenses, and create a more aggressive area. By means of leveraging system learning to higher recognize patron behavior, operational operations, and traits in the market, organizations can create proactive procedures to assume customer wishes and capitalize on opportunities. This paper will discover the capacity advantages of making use of device studying to actual-time records analysis and talk how businesses can satisfactory leverage it. The paper can even speak exceptional varieties of device gaining knowledge of strategies and do not forget some problems businesses need to do not forget before integrating system gaining knowledge of into their records evaluation systems. © 2023 IEEE.

关键词： businesses Evaluation exceptional forget records

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Proceedings of 3rd international conference on Intelligent Engineering and Management, ICIEM 2022

Proceedings of 3rd International Conference on Intelligent E...

引用

3rd international conference on Intelligent Engineering and Management, ICIEM 2022

ISBN: (纸本)9781665467568

The proceedings contain 168 papers. The topics discussed include: design for ergonomics: application of single- passenger electric car via design of experiments;detection of breast cancer using machine learning and deep learning methods;automobile insurance fraud detection: an overview;a survey on detection of lung cancer using different image processing techniques;deep learning methods for automatic number plate recognition system: a review;skin cancer detection using machine learning: a survey;transforming education system through artificial intelligence and machine learning;model for retailers with price dependent demand rates;neuromarketing: an emerging domain in the formal education system;design of dual slot microstrip antenna for wireless application;analysis of ancillary services provided by distributed energy resources in smart distribution grid;and grey scale image skeletonization of vein pattern using Hausdroff image binarization technique in biometric security system.

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Smart Vision Software application using machine learning 3

Smart Vision Software Application using Machine Learning

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3rd international conference on Artificial Intelligence and Smart Energy, ICAIS 2023

作者： Alagarsamy, Saravanan Deepak, Prudhivi Lavanya, M. Reddy, T. Gowtham Kedareswari, M. Senthil Kumar, A. Kalasalingam Academy of Research and Education Department of Computer Science and Engineering Anand Nagar Tamilnadu Krishnankoil India Aarupadai Veedu Institute of Technology Department of Mechanical and Engineering Tamilnadu India

ISBN: (纸本)9781665462167

The Smart Vision application's premise is that there are numerous rising new technologies that are excelling in their fields. The following are a few of the technologies or models that are now in use: estimation of human pose, steering angle capture, lane detection, and object detection. These are all the various approaches and superb models created with Open Pose and other tools. Since each of these systems has unique characteristics, it is vital to separately construct each one before comprehending how it works. Because there is no trial version available for consumers to use to learn how the model works, these models must be constructed using codes creating a web application that will enable students to learn about and experience how each model functions by using the camera on their device. For business professionals who can use their own models to run, deploy, and test, not simply for users. Every module on the list has some connection to autonomous navigation. These systems have been combined into a single Web application so that students may easily experiment with them and see how they work in real-time. As a result, this platform presents excellent opportunities for students and enthusiastic learners to interact with the live demo and understand how each model functions. It is believed that the Web application will serve as an excellent tool for students to experiment with and gain a feel for the operation of the aforementioned computer vision models. © 2023 IEEE.

关键词： Students

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