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2025 IEEE international Students' conference on Electrical, Electronics and computer Science, SCEECS 2025

作者： Wandile, Piyush S Singh Kirar, Bhupendra Kirar, Seema Indian Institute of Information Technology Computer Science and Engineering Bhopal India Indian Institute of Information Technology Electronics and Communications Engineering Bhopal India Bansal Institute of Science and Technology Electronics and Communications Engineering Bhopal India

ISBN: (纸本)9798331529833

Image denoising is a crucial step in image acquisition and processing that helps improve the image quality by removing the unwanted noise. In this paper Gaussian and median filters are used as denoiser and performance is evaluated using some of the key metrics like Mean Squared Error (MSE), Peak Signal-to-Noise Ratio (PSNR), Feature Similarity Index Measure (FSIM), Structural Similarity Index Measure (SSIM), Mean Absolute Error (MAE), and Correlation Coefficient. A denoiser with low MSE, high PSNR, values of 1 for SSIM, FSIM, and Correlation Coefficient. Reported results are better in comparison to existing for better image quality. © 2025 IEEE.

关键词： Wiener filtering

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Identification and Classification of Medicinal Plants using Machine Learning Algorithms 3

Identification and Classification of Medicinal Plants using ...

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3rd international conference on Electronics and Renewable Systems, ICEARS 2025

作者： Bhargavi, G. Jayaraman, Venkatesh Jabez, J. Deepa, R. Surendran, R. Srm Institute of Science and Technology Department of Computing Technologies Chennai India Chennai Institute of Technology Department of Computer Science and Engineering Chennai600069 India Sathyabama Institute of Science and Technology School of Computing Department of Computer Science and Engineering Chennai India Srm Institute of Science and Technology School of Computing Department of Computing Technologies Kattankulathur Tamilnadu Chennai603203 India Saveetha Institute of Medical and Technical Sciences Saveetha School of Engineering Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798331509675

The increaing significance of plant life and botanical expertise extends beyond mere visual appreciation. With the growing interest in sustainable living and alternative remedies, there is a pressing demand for easily accessible and credible information on plant categorization, particularly focusing on medicinal plants. This innovative project synergizes machine learning capabilities, botanical proficiency, and user-friendly technology to give users the insights required to harness the benefits of medicinal plants responsibly and sustainably. The platform facilitates precise categorization and a comprehensive understanding of the therapeutic attributes of plants. © 2025 IEEE.

关键词： Medicinal chemistry

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SMS Spam Detection using Advance Naive-Bayes Approach

SMS Spam Detection using Advance Naive-Bayes Approach

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2025 international conference on Pervasive Computational Technologies, ICPCT 2025

作者： Arora, Yojna Gupta, Neha Rathore, Yogesh Singh Bansal, Nidhi Mehta, Aina Chadha, Shikha Kumar, Ashwani Sharda University Department of Computer Science and Engineering Greater Noida India Symbiosis University of Applied Sciences School of Computer Science & Information Technology Madhya Pradesh Indore India Sharda University School of Engineering and Technology Department of Computer Science and Applications Uttar Pradesh Greater Noida India School of Engineering and Technology Department of Computer Science & Engineering Haryana Faridabad India Bennett University School of Computer Science Engineering and Technology India

ISBN: (纸本)9798331508685

Recently, with increased use of mobile phones, it has transformed into a multibillion-dollar Short Message Service or SMS. However, the drop in the cost of messaging services has led to an increased number of unsolicited commercial messages, or spam, being delivered to mobile phones. Several reasons exist for which traditional algorithms used in email filtering may not efficiently classify the spam in SMS such as the absence of strong SMS spam databases, with the short length and features of the message, the informal language used, etc. This paper uses a real SMS spam database After preprocessing the data and extraction of relevant features, Naïve Bayes machine learning techniques is applied to get the results. Then it is analyzed using confusion matrix, accuracy, precision and recall values. A learning curve with clearly defined relationship between the training and testing data set and overall error at the end. © 2025 IEEE.

关键词： Adversarial machine learning

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Design and implementation of batch file intelligent summary assistant based on AIGC+RPA 24

Design and implementation of batch file intelligent summary ...

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8th international conference on Electronic Information technology and computer engineering, EITCE 2024

作者： Lin, Meirong Information Engineering College Hainan Vocational University of Science and Technology Hainan Haikou China

ISBN: (纸本)9798400710094

This paper presents the design and implementation of a batch file intelligent summary assistant based on AIGC and RPA. This system aims to solve the problem of large human resource consumption and low efficiency in batch document processing. By combining the ability of text summary generation of AIGC technology and efficient document processing ability of RPA technology, it can realize the rapid and accurate summary of a large number of documents. This project describes in detail the overall process design of the system, the specific implementation methods of AIGC module and RPA module, summarizes the research results, and puts forward the future research direction. This study provides new ideas and technical support for improving the efficiency of batch file processing. © 2024 Copyright held by the owner/author(s).

关键词： Batch data processing

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Bibliometric and Content Analysis of Large Language Models Research in Software engineering: The Potential and Limitation in Software engineering

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international Journal of Advanced computer Science and Applications 2025年第4期16卷 344-356页

作者： Damayanti, Annisa Dwi Gani, Hamdan Zhipeng, Feng Gani, Helmy Zuhriyah, Sitti Nurani Djabir, St. Nurhayati Wardani, Nur Ilmiyanti Department of Environmental Engineering Faculty of Engineering Hasanuddin University Makassar Indonesia Department of Machinery Automation System ATI Makassar Polytechnic Makassar Indonesia School of Culture Creativity and Media Hangzhou Normal University Zhejiang Hangzhou China Department of Industrial Hygiene Faculty of Public Health Occupational Health and Safety Makassar College of Health Sciences Indonesia Department of Computer System Universitas Handayani Makassar Makassar Indonesia Department of Information Systems and Technology Institut Teknologi dan Bisnis Nobel Indonesia Jl. Sultan Alauddin No.212 Makassar90221 Indonesia Department of Informatics Engineering Universitas Handayani Makassar Makassar Indonesia

Large Language Models (LLM) is a type of artificial neural network that excels at language-related tasks. The advantages and disadvantages of using LLM in software engineering are still being debated, but it is a tool that can be utilized in software engineering. This study aimed to analyze LLM studies in software engineering using bibliometric and content analysis. The study data were retrieved from Web of Science and Scopus. The data were analyzed using two popular bibliometric approaches: bibliometric and content analysis. VOS Viewer and Bibliometrix software were used to conduct the bibliometric analysis. The bibliometric analysis was performed using science mapping and performance analysis approaches. Various bibliometric data, including the most frequently referenced publications, journals, and nations, were evaluated and presented. Then, the synthetic knowledge method was utilized for content analysis. This study examined 235 papers, with 836 authors contributing. The publications were published in 123 different journals. The average number of citations per publication is 1.44. Most publications were published in Proceedings international conference on Software engineering and ACM international conference Proceeding Series, with China and the United States emerging as the leading countries. It was discovered that international collaboration on the issue was inadequate. The most often used keywords in the publications were "software design," "code (symbols)," and "code generation." Following the content analysis, three themes emerged: 1) Integration of LLM into software engineering education, 2) application of LLM in software engineering, and 3) potential and limitation of LLM in software engineering. The results of this study are expected to provide researchers and academics with insights into the current state of LLM in software engineering research, allowing them to develop future conclusions. © (2025), (Science and Information Organization). All Rights Res

关键词： Software design

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Research on brain signal acquisition and transmission via non-invasive brain-computer interface 3

Research on brain signal acquisition and transmission via no...

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3rd international conference on Algorithms, Network, and Communication technology, ICANCT 2024

作者： Luo, Weihao Xiong, Shiyi Li, Yan Jiang, Pan School of Information Engineering Wuhan Business University Hubei Wuhan430000 China

ISBN: (数字)9781510688902

ISBN: (纸本)9781510688896

Non-invasive brain-computer interface technology has become a research hotspot in the field of human-computer interaction with its characteristics of no surgery and safe reliability. This paper introduces the non-invasive brain signal acquisition and transmission of brain-computer interface technology, which aims to enable people with disabilities to conduct peripheral control through thinking. Brain wave signals were collected by using electroencephalography (EEG) technology and functional magnetic resonance imaging (fMRI) technology. This paper focuses on the use of brain signal analysis, correlation function analysis and independent component analysis (ICA) to collect the signal for comprehensive noise processing and artifact processing, and finally the processed signal instructions are transmitted to the corresponding peripherals to control it. The device not only has the function of signal collection and transmission, but also can be customized according to the needs of users to complete the function of fitting the user, which can effectively help the disabled to live independently and improve the quality of life. © 2025 SPIE.

关键词： Brain computer interface

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Efficient Deployment Using CI/CD: Text Summarization Using NLP in Cloud 1

Efficient Deployment Using CI/CD: Text Summarization Using N...

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1st international conference on AIML-Applications for engineering and technology, ICAET 2025

作者： Shingade, Bhuvan Hariharan, Siddharth Patole, Amol Singh, Kishan TPCT's Terna Engineering College Department of Computer Engineering Mumbai India Watumull Institute of Electronics Engineering and Computer Technology Department of Computer Engineering Mumbai India

ISBN: (纸本)9798350355611

The core task in natural language processing (NLP) is text summarization, which condenses important information from large volumes of text into brief summaries. This study reviews text summarization strategies using NLP principles, focusing on two main methods: extractive and abstractive summarization. Abstractive techniques generate summaries by interpreting and rephrasing information, while extractive methods highlight key sentences or paragraphs from the original text. Our study examines various algorithms and models within both paradigms, leading to the development of a novel summarization model. Inspired by advancements in deep learning and transformer architectures, our model integrates state-of-the-art techniques to produce high-quality summaries. We discuss the architecture, training, and evaluation of our model, demonstrating its effectiveness on benchmark datasets. Lastly, we explore potential applications and future directions, emphasizing the importance of custom-built solutions for modern information processing tasks. © 2025 IEEE.

关键词： Inverse problems

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A Comprehensive Analysis on Severity Estimation of Plant Diseases by Deep Learning Models

A Comprehensive Analysis on Severity Estimation of Plant Dis...

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2025 IEEE international conference on Computational, Communication and Information technology, ICCCIT 2025

作者： Sonu Varghese, K. Kumar, R. Satheesh Sahrdaya College of Engineering and Technology APJ Abdul Kalam Technological University Kerala Department of Computer Science and Engineering India Jawaharlal College of Engineering and Technology APJ Abdul Kalam Technological University Department of Computer Science and Engineering Kerala India

ISBN: (纸本)9798331512965

The rapid spread of diseases and pest infestations has a detrimental effect on plant health. Methods for disease classification and detection have gained new insights from the developments in computer vision and deep learning approaches. However, there has been relatively limited work in the area of severity estimation and disease progression rate since it requires more detailed information such as the percentage of affected leaf area, symptoms intensity, and environmental factors that lead to the disease progression over time. Thus the modern agricultural sector faces a significant difficulty in the assessment of plant disease severity and tracking of disease development. The purpose of this study is to perform a thorough review of various deep learning methods for plant disease severity assessment, taking into account factors like accuracy, severity level measurement, and dataset employed. The article also suggests ways to address the shortcomings of the current approach. © 2025 IEEE.

关键词： Adversarial machine learning

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Research on Driving Behavior Detection Algorithm Based on YOLOv10 24

Research on Driving Behavior Detection Algorithm Based on YO...

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8th international conference on Electronic Information technology and computer engineering, EITCE 2024

作者： Luo, Dongsong Cai, Gengchen Lan, Yiting School of Electrical Engineering and Information Engineering Lanzhou University of Technology Gansu Lanzhou China

ISBN: (纸本)9798400710094

To address low accuracy and slow speed in detecting abnormal driving behaviors during daily driving, we propose YOLOv10nDBD, based on the YOLOv10n baseline model. It integrates the lightweight G-ghostNet for the backbone, enhancing efficiency. The addition of the NAMA-Attention module reduces computational load. To tackle issues with small object detection like cigarettes, DSConv replaces traditional convolutions, improving efficiency. Experimental results show YOLOv10n-DBD improves mAP50 by 5.1%, reduces parameters by 23.4%, and decreases GFLOPs by 13.4% compared to YOLOv10n, enhancing both accuracy and real-time performance in detecting abnormal driving behaviors. © 2024 Copyright held by the owner/author(s).

关键词： Object detection

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Research on Digital Watermarking Algorithm Based on Wavelet Transform Fused with Visual Model 24

Research on Digital Watermarking Algorithm Based on Wavelet ...

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8th international conference on Electronic Information technology and computer engineering, EITCE 2024

作者： Yu, Fei School of Electrical and Electronic Engineering Guilin Institute of Information Technology Guilin China

ISBN: (纸本)9798400710094

This paper aims to develop a digital watermarking algorithm based on wavelet transform and the characteristics of the human visual system (HVS). The main objective is to leverage the masking characteristics of HVS and the time-frequency localization properties of wavelet transform to achieve efficient watermark embedding. The goal is to ensure that the watermark is imperceptible to the human eye while maintaining the robustness and embedding strength of the watermark. This research contributes to enhancing the practicality and reliability of digital image processing and information security technologies. © 2024 Copyright held by the owner/author(s).

关键词： Embeddings

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