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检索条件"任意字段=2023 International Conference on Computer Science and Automation Technology, CSAT 2023"

共 68823 条记录，以下是1271-1280 订阅

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Machine Learning Based Improved Phishing Detection using Adversarial Auto Encoder

Machine Learning Based Improved Phishing Detection using Adv...

引用

2023 international conference on System, Computation, automation and Networking, ICSCAN 2023

作者： Balaji, S. Sathishkumar, R. Sharmila, G. Arikaran, N. Nivas, K. Dhamotharan, S. Manakula Vinayagar Institute of Technology Department of Computer Science and Engineering Puducherry India

ISBN: (纸本)9798350315127

Phishing scams are frequently used by malicious actors to get login credentials from unsuspecting users. One method for detecting phishing is machine learning. Despite the fact that the accuracy of machine learning algorithms is mostly determined by the training data, there isn't much easily accessible attack data. We present a method for enhancing the datasets used by machine learning algorithms. We create samples that resemble phishing websites using an Adversarial Auto Encoder (AAE) and offer metrics to judge the effectiveness of the samples. We compare these samples to models created from actual data. Some of the created samples could be impossible for the current model to recognize. After that, training is done with the remaining samples. Improved levels of accuracy and reliability are provided by the upgraded machine learning models. In other words, phishing detection is improved during model construction by merging data from real phishing sites with AAE fake data. © 2023 IEEE.

关键词： Websites

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Ground Plane Segmentation and Outliers Removal in Point Clouds of Electrical Substations 3

Ground Plane Segmentation and Outliers Removal in Point Clou...

引用

3rd IEEE international conference on Information technology, Big Data and Artificial Intelligence, ICIBA 2023

作者： Wang, Fei Fan, Zikai Li, Yan Xu, Lai Shi, Liang Qian, Kun Economic Research Institute State Grid Jiangsu Electric Power Co. Ltd. Nanjing China Southeast University School of Automation Nanjing China

ISBN: (纸本)9781665490788

With the increasing popularity of 3D laser scanning technology, automatic modeling of 3D point clouds of substation scenes is crucial for applications such like the digitalization of electrical substations. However, the point clouds obtained by the 3D laser scanner is noisy. In addition to the equipment that needs to be extracted, it also contains ground plane data, vegetation data, power lines, and others. In this paper, we propose a ground plane segmentation and outliers removal method as a fundamental step toward substation entity modeling. In particular, we have developed an automatic ground plane removal method and an interactive method for removing outliers. Finally, the effectiveness of the model proposed in this paper is validated through a case study in a substation point cloud. © 2023 IEEE.

关键词： Three dimensional computer graphics

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An IoT Solutions for Ungulates Attacks in Farmland 2

An IoT Solutions for Ungulates Attacks in Farmland

引用

2nd international conference for Innovation in technology, INOCON 2023

作者： Raju, Ratheesh Thasleema, T.M. Central University of Kerala Department of Computer Science Kasaragod Periye India

ISBN: (纸本)9798350320923

Agriculture is considered to be a significant contributor to the global financial system and human diets. It has been recognized as the country's primary source of income and employment. So, it's really important to protect crops from various dangerous hazards, such as diseases, insects, bird and animal attacks, high atmospheric temperature, etc., and also from weak irrigation systems, poor soil quality, weeds management, etc. Specific insect attacks and diseases have long been a primary crop sector concern. computer vision (CV)-based automatic insect and disease detection methods are used in smart farming systems because of their high cost-effectiveness and efficient automation. This paper gives an overview of the use of Machine Learning (ML), Deep Learning (DL), and the Internet of Things (IoT) in agriculture to protect crops from various dangerous hazards and proposes an automatic Animal-Repelling System (ARS). This study implements a system based on IoT to protect crops from animals. The proposed low-cost agricultural field protection system helps farmers to protect their crops and increase production yield and income. © 2023 IEEE.

关键词： Internet of things

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Apple Automatic Classification Method Based on Improved VGG11 3

Apple Automatic Classification Method Based on Improved VGG1...

引用

3rd international conference on computer Vision and Pattern Analysis, ICCPA 2023

作者： Wang, Jianxia Zhang, Hongjiao Zhou, Wanzhen School of Information Science and Engineering Hebei University of Science and Technology Shijiazhuang China

ISBN: (纸本)9781510667563

In order to solve the problem that traditional fruit grading methods are easy to cause damage to fruits and low grading accuracy, taking apple grading as an example, transfer learning is used to pre-train the data-enhanced dataset, and an adaptive pooling layer is added to the Feature layer of the original VGG11 model, and then an SE module based on attention mechanism is added between the adaptive pooling layer and the Classifier layer to increase the weight of the effective feature map and reduce the weight of the invalid or small feature map. In order to make the training model get better results, thereby improving the accuracy of the algorithm. Comparing the improved model with GoogleNet model, LeNet-5 model, etc., the SE-VGG11 model has the best effect, the classification accuracy can reach 98.53%, and an Apple grading time only takes 0.1s, which can meet the needs of factory automation classification. In summary, the improved model can be used for efficient grading of apples. © 2023 SPIE.

关键词： Grading

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Text Analysis Tool

Text Analysis Tool

引用

2023 international conference on Artificial Intelligence and Applications, ICAIA 2023 and Alliance technology conference, ATCON-1 2023

作者： Noronha, Perpetua F. Bhan, Madhu Niranjanamurthy, M. Chandana, D. Mount Carmel College Autonomous Department of Computer Science Bangalore India M.S.Ramaiah Institute of Technology Department of Mca Bangalore India B.M.S. Institute of Technology Department of Ai and Ml Bangalore India Utegration Company Department of Software Development Bangalore India

ISBN: (纸本)9781665456272

The automated analysis of electronic text is referred to as 'text processing'. The amount of online textual data is increasing, and automatic text processing techniques have the potential to be tremendously beneficial because they can gather more meaningful information faster. Features like text summarization, language translation, emotion classifier and headline generation of news articles are some of the popular ways of text processing. The fundamental goal of text summarization is to extract the most important information from a text and deliver it in a concise and legible form. The practice of transforming written text from one language into another such that it may be easily understood is known as language translation. Emotion classifier analyses the emotions and categorizes the text into various emotions. Headline generation is the process of obtaining the headlines from various news articles. This paper is about developing a text processing tool based on the concepts of Machine Learning and Natural Language Processing. Implementation of this tool allows for the automation of text processing. This tool aims to improve productivity and efficiency of processed data by faster generation of precise and meaningful data to all the providers across all platforms. © 2023 IEEE.

关键词： Text processing

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Digital Modeling and Dynamic Simulation of Pressurization Feed System 9

Digital Modeling and Dynamic Simulation of Pressurization Fe...

引用

9th international conference on Fluid Power and Mechatronics, FPM 2023

作者： Xue, Zhuwen Yuan, Mei Qu, Yufeng Dong, Shaopeng Zhang, Sihan School of Automation Science and Electrical Engineering Beihang University Beijing China School of Automation Science and Electrical Engineering Ningbo Institute of Technology Beihang University Beijing China Research Institute for Frontier Science Beihang University Beijing China

ISBN: (纸本)9798350304947

Liquid rocket pressurization feed system is an important part of the rocket power system, and its main function is to achieve the supply of propellant. With the continuous improvement of space technology, the technical requirements of pressurization feed system are also increasing. Based on the modular modeling and simulation method, the article establishes detailed simulation models of the pressure reducing valve and switching valve using the PCD(Pneumatic Component Design) library in AMESim, analyzes the influence of the main parameters on the performance of the valve, establishes the digital model and studies the influence of the system, provides reference for the valve parameter selection and performance optimization, and helps to save time and cost for the development and design of the pressurization feed system. © 2023 IEEE.

关键词： Digital libraries

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Enhancing Model Reference Adaptive Control through Error Prediction using Phase Space Reconstruction and GRU Network

Enhancing Model Reference Adaptive Control through Error Pre...

引用

2023 international conference on automation, Control and Electronics Engineering, CACEE 2023

作者： Xiong, Yao Fei, Minrui Wang, Haikuan Wang, Aimin Shanghai University Shanghai Key Laboratory of Power Station Automation Technology School of Mechatronic Engineering and Automation Shanghai China

ISBN: (纸本)9798350309201

In this paper, a novel approach is proposed to enhance model reference adaptive control (MRAC) systems by incorporating error prediction through phase space reconstruction (PSR) and a gated recurrent unit (GRU) neural network. Traditional adaptive control systems often struggle with unpredictable disturbances and uncertainties in dynamic processes. Here, we leverage the power of phase space reconstruction to capture underlying system dynamics and employ a GRU network to predict future error states. By integrating these techniques into adaptive control, our proposed method demonstrates superior adaptability and robustness, enabling more efficient and reliable control in complex and uncertain environments. Experimental findings confirm the efficacy of the suggested strategy, highlighting its potential for complex real-world applications. © 2023 IEEE.

关键词： Model reference adaptive control

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Bridging Automated Reasoning and Machine Learning for Information Analysis 2

Bridging Automated Reasoning and Machine Learning for Inform...

引用

2nd IEEE international conference on Futuristic Technologies, INCOFT 2023

作者： Joshi, Sarita Murugan, R. Balaji, N.V. Chandrakala, P. Deshmukh, Gopal B. Mathur, Mala Maharishi School of Business Management Maharishi University of Information Technology Uttar Pradesh India Bangalore Department of Computer Science and Information Technology Karnataka India Karpagam Academy of Higher Education Department of Computer Science Coimbatore641021 India Prince Shri Venkateshwara Padmavathy Engineering College Department of Electrical and Electronics Engineering Chennai127 India Vishwakarma Institute of Information Technology Department of Computer Engineering Pune India Vivekananda Global University Department of Civil Engineering Jaipur India

ISBN: (纸本)9798350308846

Recent advances in automated reasoning and system studying have appreciably impacted the automation of statistics evaluation. These technologies facilitate understanding the increasingly more complicated volumes of facts in a ramification of approaches. Automatic reasoning helps decide valid solutions based on structured good judgment, while machines can pick out patterns and developments in massive datasets. Bridging those two technologies improves accuracy and efficiency in automated facts evaluation. This paper will overview present-day research on bridging automated reasoning and device-gaining knowledge for such purposes and gift novel approaches to combining the two technologies for more effective data evaluation. Discussion subjects will encompass integrating neural networks and reasoning engines, methods for addressing records incompleteness and uncertainty, and enhancement of reasoning-driven context-conscious systems. Furthermore, the paper will discover the capacity benefits that can be performed via leveraging the strengths of each automated reasoning and gadget gaining knowledge of to optimize answers for a selection of software scenarios. © 2023 IEEE.

关键词： Gaining Optimize Reasoning Selection Uncertainty

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Track-to-Track Association Based on Modified Covariance Intersection for Multi-target Tracking 12

Track-to-Track Association Based on Modified Covariance Inte...

引用

12th IEEE international conference on Control, automation and Information sciences, ICCAIS 2023

作者： Cong, Jinliang Xu, Benlian Lu, Mingli Shi, Jian Jiang, Teng Li, Yinya Gu, Suhang Sheng, Andong Changshu Institute of Technoloy School of Electrical Engineering and Automation Suzhou China Suzhou University of Science and Technology School of Electronic and Information Engineering Suzhou China Qufu Normal University School of Mathematical Sciences Qufu China Nanjing University of Science and Technology School of Automation Nanjing China

ISBN: (纸本)9798350328783

In this paper, a CI (Covariance Intersection) based track-to-track association algorithm is proposed for the case where the cross-covariance is unknown in distributed multi-target tracking system. CI is used to compute the association statistics, which avoids the computation of cross-covariance among the nodes and improves the usability of the algorithm. In addition, a fast CI algorithm is introduced to further reduce the communication and computational burden between nodes. Finally, simulation examples are provided to verify the effectiveness of the proposed algorithm. © 2023 IEEE.

关键词： Clutter (information theory)

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Discovery of Unknown Classes in Constrained Semi-Supervised Learning 2

Discovery of Unknown Classes in Constrained Semi-Supervised ...

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2nd international conference on Advancements in Electrical, Electronics, Communication, Computing and automation, ICAECA 2023

作者： Roopa, S. Nithya Department of Computer Science and Engineering Kumaraguru College of Technology Coimbatore India

ISBN: (纸本)9798350306811

Supervised classification models have proved their significance in research and are utilized in many key areas. However, there are some limitations for these methods. In supervised learning, adequate labelled training data are required for each class. The learned classifier can classify only the data belonging to classes for which training data is available and lacks the ability to handle the data of unseen classes. However, in real time scenarios, there may not be adequate training data for all the classes. There could also be scenarios where the classes not available in the training data appearing in the testing data. The learner is expected to have the capability to uncover the class labels for the data belonging to unseen classes. To handle this situation, methods under different learning paradigms are proposed. In this work, various semi supervised learning techniques that can handle hidden classes(clusters) are evolved. Variant of Semi Supervised EM Based-K means and Naïve Bayes are discussed. © 2023 IEEE.

关键词： Classification (of information)

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