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检索条件"机构=Dept. of Computer Science Engineering and Applications"

共 35530 条记录，以下是81-90 订阅

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NLP based Text Summarization Techniques for News Articles 2

NLP based Text Summarization Techniques for News Articles

引用

2nd IEEE International Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation, IATMSI 2024

作者： Kumaran, B. Logesh Ravindran, N.V. Dept. of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350360523

This defines a news summarization web application using Streamlit, allowing users to access and read news articles from various sources. Here's an abstract of what the project does the necessary Python libraries are imported, including Streamlit for the web application, BeautifulSoup for web scraping, PIL for image processing, and Newspaper for article extraction. Three functions are defined for fetching news based on different criteria: fetch-news-search-topic for searching news based on a topic, fetch-top-news for fetching the top news, and fetch-category-news for fetching news based on a specific category. A function, fetch-news-poster, is defined to fetch and display the image associated with each news article. The display-news function is defined to present the news articles on the Streamlit web application, along with their associated images, summaries, and publication dates. The run function configures the Streamlit application layout and functionality, including options for selecting news categories, displaying trending news, choosing favorite topics, and searching for specific topics. The application displays a title, logo, and various news categories, allowing users to select their preferred category and view the corresponding news articles. Overall, this application provides a convenient way for users to access and read summarized news articles based on their preferences. © 2024 IEEE.

关键词： Image processing

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An Evaluation and Comparison for Phishing Attack Detection using Machine Learning Approaches 3

An Evaluation and Comparison for Phishing Attack Detection u...

引用

3rd International Conference on Power Electronics and IoT applications in Renewable Energy and its Control, PARC 2024

作者： Sharma, Ajeet Kumar Anushree Rakesh, Nitin Verma, Pawan Kumar Sharda University School of Engineering and Technology Dept. of Computer Science & Engineering Uttar Pradesh Greater Noida India GLA University Dept. of Computer Engineering & Applications Uttar Pradesh Mathura India Nagpur Campus Pune India

ISBN: (纸本)9798350309409

The persistent and evolving threat of phishing attacks demands effective and adaptive detection techniques. This research paper presents a comprehensive evaluation and comparison of various machine learning approaches to detect phishing attacks. We investigated five prominent algorithms: Logistic Regression, Support Vector Machine (SVM), K-Nearest Neighbors (K-NN), Naive Bayes, and Extreme Gradient Boosting (XGBoost), to determine their efficacy in identifying phishing activities. Our methodology involved a systematic analysis using a large dataset of phishing and legitimate URLs, where each model was trained, tested, and validated to ensure robustness and reliability. The performance of each algorithm was assessed based on accuracy, precision, recall, and F1 score. Among the evaluated models, XGBoost demonstrated superior performance, achieving an exceptional accuracy of 99.75%. This result underscores the potential of XGBoost in phishing attack detection, offering a promising tool for cybersecurity applications. © 2024 IEEE.

关键词： Cybersecurity

来源：评论

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Quantum Network Routing with Heterogeneous Nodes 17

Quantum Network Routing with Heterogeneous Nodes

引用

17th International Conference on COMmunication Systems and NETworkS, COMSNETS 2025

作者： Pandey, Anoop Kumar Tamma, Bheemarjuna Reddy Rao, M.V. Panduranga IIT Hyderabad Dept. of Computer Science and Engineering India

ISBN: (纸本)9798331531195

Deciding a route for the transfer of quantum information (namely, qubits) on a quantum network is a significant problem that is being studied extensively. In this work, we investigate the problem of routing on a quantum network of heterogeneous nodes both with and without fidelity and timing *** propose a Path Request Packet (PRP) based routing scheme for dynamically selecting a path that maximizes the overall probability of transmission success while maintaining fidelity above a threshold and adhering to time constraints. While the proposed scheme can perform suboptimally under fidelity and timing constraints, we discuss a straightforward proof of optimality in the absence of these constraints. Simulations on random graphs demonstrate that the PRP-based scheme performs better, both in terms of reliability and fidelity, than a non-trivial baseline routing algorithm. © 2025 IEEE.

关键词： Quantum electronics

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Machine Learning Techniques for Predicting Ovarian Cancer in its Early Stages Using Biomarkers 6

Machine Learning Techniques for Predicting Ovarian Cancer in...

引用

6th International Conference on Electrical engineering and Information and Communication Technology, ICEEICT 2024

作者： Alam, Mir Jafikul Anawar, Jannat-E Mohi Uddin, Khandaker Mohammad Rahman, Md. Hasibur Rahman, Md. Mahbubur Dhaka International University Dept. of Computer Science and Engineering Dhaka Bangladesh Southeast University Dept. of Computer Science and Engineering Dhaka Bangladesh Bangladesh University of Business and Technology Dept. of Computer Science and Engineering Dhaka Bangladesh

ISBN: (纸本)9798350385779

The deadliest gynecological cancer affecting women is ovarian cancer, currently incurable with no effective medication treatments. The key focus of this research is to assess insights for early diagnosis using statistical analysis and machine learning techniques on data from clinical trials obtained from 349 patients. Several techniques, including Random Forest, Decision Tree, Gaussian NB, AdaBoost, and Logistic regression, were applied to find the most reliable factor for ovarian cancer prediction. A clinically evaluated raw dataset of benign samples and malignant ovarian tumor patient data set is used to develop early-stage ovarian cancer predictions, and the effectiveness of ML models was examined utilizing metrics including F1-score, Accuracy, Precision, and Recall. The proposed study shows better outcomes, with the Random Forest classifier exhibiting the highest accuracy for validation at 99% based on the test data of ovarian cancer predictions. Even though early-stage ovarian cancer detection is generally unavailable, cancer diagnosis may be greatly aided by machine learning. © 2024 IEEE.

关键词： Machine learning

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Digital Solutions for Crime Control: A Comprehensive Criminal Identification and Reporting Framework 11

Digital Solutions for Crime Control: A Comprehensive Crimina...

引用

11th International Conference on Reliability, Infocom Technologies and Optimization, ICRITO 2024

作者： Harinee, S. Anand, M. Vijay Dept. of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350350357

This paper presents the design and implementation of a comprehensive Criminal Identification and Reporting System (CIRS) aimed at enhancing law enforcement capabilities and improving public safety. The system enables users, including victims and law enforcement officers, to submit and manage complaints seamlessly through an intuitive online platform. Key features include the storage of user data in a secure database, real-time monitoring of criminal activity using CCTV footage, and advanced facial recognition technology for swift identification of potential offenders. The CIRS facilitates efficient case management by allowing users to track the status of their complaints and providing law enforcement agencies with valuable information to aid in criminal investigations. Moreover, the system assists local government agencies in maintaining records of known criminals, enabling proactive measures to prevent illegal activities. By leveraging cutting-edge technology and providing seamless integration with existing surveillance infrastructure, the CIRS promises to revolutionize criminal identification and reporting processes, ultimately contributing to improved public safety and law enforcement efficiency. © 2024 IEEE.

关键词： Face recognition

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A Black-box based Attack Generation Approach to Create the Transferable Patch Attack 7

A Black-box based Attack Generation Approach to Create the T...

引用

7th International Conference on Intelligent Computing and Control Systems, ICICCS 2023

作者： Agrawal, Khushabu Bhatnagar, Charul GLA University Dept. of Computer Engineering and Applications Mathura India

ISBN: (纸本)9798350397253

Due to the recent advancement of deep learning methodologies, face recognition has seen increased success. However, researchers found that adversarial attacks can be launched against deep learning-based systems. The face recognition systems can be tricked by small changes in an input image. The human visual system is incapable of detecting these changes. In this work, a black-box attack generation method is proposed to create a transferable patch attack (TPA) using the generative adversarial network (GAN) to deceive the current face recognition systems. The generator and discriminator networks are used in the TPA attack to generate the adversarial images. The Labeled Face in the Wild (LFW) dataset is used as input for the proposed TPA attack, which creates the image by adding noise in the form of a patch. These patches are added in such a manner that they are invisible to the naked eye. FaceNet, ArcFace and CosFace face recognition models are used for the attack testing and also the proposed attack is compared to existing attacks. The purpose of this paper is to suggest a black-box attack and increase the transferability of adversarial attacks. In the black-box attack, the attacker doesn't know any information about the target model. The quantitative findings demonstrate that the proposed attack successfully misclassified the most recent FR models and achieved a higher attack success rate. © 2023 IEEE.

关键词： Face recognition

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Ensemble model for Detecting Phishing and Trojan using Latest Machine Learning Techniques 12

Ensemble model for Detecting Phishing and Trojan using Lates...

引用

12th IEEE International Conference on Communication Systems and Network Technologies, CSNT 2023

作者： Agrawal, Rahul Rathor, Sandeep Agrawal, Khushabu Gla University Dept. of Computer Engineering and Applications Mathura India

ISBN: (纸本)9781665462617

Machine learning is significant fourth industrial revolution technology that may be habitual to defend Internetconnected devices against cyber threats, assaults, damage, or illegal access. Cyber security computing may become more automated and intelligent than conventional security systems due to security intelligence modeling. Using an ensemble model of machine learning and deep learning, the objective of the proposed work is to identify phishing and Trojan attacks. In this ensemble method, we used the VGG-16 and Random Forest classifier and evaluate the performance to detect the attack. In this work, we have also shown the comparison of the proposed method with the existing attack. © 2023 IEEE.

关键词： Cybersecurity

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Machine Learning Classifiers for Predicting the Risk of Cardiovascular Disease in Healthcare 4.0 3

Machine Learning Classifiers for Predicting the Risk of Card...

引用

3rd International Conference on Communication, Control, and Intelligent Systems, CCIS 2024

作者： Kumari, Palak Kumar, Ashish Chatterjee, Kakali Master of Computer Applications Patna Women's College Patna India National Institute of Technology Patna Dept. of Computer Science and Engineering Patna India

ISBN: (纸本)9798331528201

Cardiovascular disease (CVD) generic phrase used to describe heart or blood vessel illness. Conditions that impact the body's, brain's, or heart's blood flow. Reduced blood flow can result from factors such as blood clots, leading to heart attack, angina, or stroke. Other potential meanings of CVD. These models offer key benefits like clear interpretability and the ability to analyze complex patterns, significantly enhancing the accuracy of cardiovascular disease risk predictions. The demerits of using SVM, LR, K-NN, and MLP for CVD prediction include inter-pretability issues, overfitting risks, data requirements, feature selection challenges, scalability concerns, algorithm complexity, and class imbalance. Collaboration between machine learning experts and healthcare professionals is essential for developing accurate and reliable CVD prediction models that enhance patient care. CVD is a significant health threat, often leading to fatal complications. Early detection is crucial for effective intervention. This study employs SVM (accuracy is 0.84%), LR (accuracy is 0.86%), K-NN (accuracy is 0.94%), and MLP (accuracy is 0.79%) machine learning techniques to enhance CVD detection by addressing outliers and null values, contributing to advancing automatic detection initiatives. © 2024 IEEE.

关键词： Nearest neighbor search

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Hindi News Article's Headline Generation based on Abstractive Text Summarization

Hindi News Article's Headline Generation based on Abstractiv...

引用

2023 IEEE International Conference on Network, Multimedia and Information Technology, NMITCON 2023

作者： Kumar, Jeetendra Shekhar, Shashi Gupta, Rashmi Atal Bihari Vajpayee University Dept. of Computer Science and Application Bilaspur India Gla University Dept. of Computer Engineering and Applications Mathura India

ISBN: (纸本)9798350300826

Text summarization is a technique that converts large text into shorter ones by keeping its important information. Most of the available summarizers, summarize English language text. The availability of summarizers in other languages is rare. In the proposed work, abstractive text summarization (ATS) for the Hindi language has been used to generate headlines from news text. To build the model, a Hindi news dataset has been used that contains different news articles related to sports, politics, crime, etc. After pre-processing the text, Word2Vec method has been used for word embedding. ATS model has been built using the Seq2Seq model with attention. After that, we have calculated evaluation metrics like ROUGE and BLEU scores of the result summaries. We have also fine-tuned two pre-trained models, indicBART and multi-lingual variant of T5. After result comparison, it was found that the indicBART perform better than the other two models, considered for the experiment. © 2023 IEEE.

关键词： Text processing

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A Survey on Aspect-based Sentiment Analysis for Online Purchased Product Feedback 10

A Survey on Aspect-based Sentiment Analysis for Online Purch...

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17th INDIACom;2023 10th International Conference on Computing for Sustainable Global Development, INDIACom 2023

作者： Prakash, Yuvraj Sharma, Dilip Kumar Gla University Dept. of Computer Engineering and Applications Mathura India

ISBN: (纸本)9789380544472

Customer review can have a significant impact on the development of a product and the innovations that need to be done in it from time to time. Nowadays, it is really easy to get customer reactions. The organization may examine user opinions that are favorable or unfavorable about the product in the feedback or comments sections of social media and online retail platforms. As the success or failure of a product is directly tied to how well consumers like it, understanding their opinions may help businesses prepare for the future and improve their products. In this research, we explored studies that used aspect-based sentiment analysis to assess user opinions of online sold items. This method employs aspect terms by determining a connection between the terms to analyze the sentiment of the feedback. It means analyzing customer comments and statements about a product and drawing meaning from them. We have discussed articles from the last five years that analyzed the sentiment using Aspect based Sentiment Analysis on social media and e-commerce media. © 2023 Bharati Vidyapeeth, New Delhi.

关键词： Sentiment analysis

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