检索结果-内蒙古大学图书馆

1st International Conference on Innovations in Communications, Electrical and computer Engineering, ICICEC 2024

作者： Deepa, R. Jayalakshmi, V. Thilakavathy, P. Manikandan, G. Surendran, R. SRM Institute of Science and Technology School of Computing Department of Computing Technologies Chennai India SRM Institute of Science and Technology Department of Computer Science and Applications Ramapuram Chennai India Vels Institute of Science and Engineering Vels Institute of Science Technology and Advanced Studies Chennai India Anna University St. Joseph's College of Engineering Department of Artificial Intelligence and Machine Learning Chennai India Saveetha Institute of Medical and Technical Sciences Saveetha School of Engineering Department of Computer Science and Engineering Chennai India

ISBN: (数字)9798350376517

ISBN: (纸本)9798350376517

Automated speech recognition (ASR) systems struggle with Bengali, which is the fifth most spoken language. Bengali has a varied morphology, many dialects, and limited high-quality annotated voice data. Traditional voice recognition techniques work well however struggle with Bengali phonetics and syntax. This method eliminates the need for large amounts of tagged data and the difficulties of differentiating sounds in different languages, both issues are addressed by this procedure. The research in this paper offers an Intellectual Bengali Speech Recognition System using Deep Learning Techniques (IBSRS-DLT). The model in this system uses transformer architecture and attention processes to manage Bengali speech pattern long-range dependencies. The IBSRS-DLT outperforms standard models in recognition accuracy using a pre-trained transformer model modified for phonetic and lexical correctness and fine-tuned on Bengali datasets. After training on a vast Bengali speech corpus, real-world datasets and rigorous simulations confirm the system. IBSRS-DLT can be used for automatic transcription, voice-controlled devices, and Bengali virtual assistants, such applications are efficient and accessible. The simulation showed a considerable boost in recognition speed and a decrease in keyword mistakes compared to current methods. This paper shows that deep learning can solve linguistic issues in ASR systems, enabling scalable regional language detection. © 2024 IEEE.

关键词： Deep learning

来源：评论

学校读者我要写书评

暂无评论

Leveraging Deep Learning Models for Machine-Generated Text Detection Using Transformer-Based Models

Leveraging Deep Learning Models for Machine-Generated Text D...

引用

2024 International Conference on Innovative computing, Intelligent Communication and Smart Electrical Systems, ICSES 2024

作者： Suthanthiradevi, P. Revathy, G. Rejini, K. Muthu Lakshmi, V. School of Computing Srm institute of Science and Technology Department of Data Science and Business Systems Kattankulathur Chennai India Vels Institute of science Technology and Advanced studies Department of Computer science and engineering Chennai117 India Amrita college of Engineering and Technology Department of Computer Science Engineering Nagercoil India St. Joseph's College of Engineering Department of Computer Science and Engineering OMR Chennai India

ISBN: (纸本)9798331543617

GPT is a large language model (LLM) derived from natural language processing that can generate a human-like text using machine learning. However, these models raise questions about authenticity and reliability of material, particularly in fields such as journalism, social media, and academia, despite their usefulness for automating text-based tasks. Detecting machine-generated text is thus an important difficulty in ensuring content integrity. This study investigates the use of huge language models as a technique for recognizing machine-generated material. The author proposes a comprehensive detection model by evaluating the language patterns, syntactic structures, and stylistic traits that separate AI-generated literature from human writing. In addition, this research investigate the possibilities of fine-tuning models designed expressly for text identification tasks and evaluate their performance using LLM - Detect AI Generated Text datasets. In digital ecosystems, LLMs are effective at detecting AI-generated text, providing a novel approach for content moderation, academic integrity checks, and synthetic media detection. An increasingly AI-powered future will require a model that can discriminate between human and machine-generated writing in real-time. According to experimental findings, the CNN architecture's design combined with the use of DistilBERT embeddings allows for the effective and efficient classification of AI generated text data, achieving an exceptional 98% accuracy rate. © 2024 IEEE.

关键词： Adversarial machine learning

来源：评论

学校读者我要写书评

暂无评论

A Comprehensive Review on the Prediction of Video Frame and Motion Contents

A Comprehensive Review on the Prediction of Video Frame and ...

引用

2024 International Conference on Integration of Emerging Technologies for the Digital World, ICIETDW 2024

作者： Mohana Priya, P. Ulagapriya, K. Vels Institute of Science Technology and Advanced Studies Department of Computer Science and Engineering Chennai India

ISBN: (数字)9798331541170

ISBN: (纸本)9798331541187

The capability of predicting, or analyzing the future outcomes of motion pictures using intelligent systems is the video frame prediction process. Video frame prediction is a significant and challenging aspect of computer Vision (CV) applications. Video prediction plays a vital role in terms of robotics and Artificial Intelligence (AI) applications in detecting the future frames of a video, depending on which, the decision-making process can be carried out. The existing video frame prediction processes include pixel law based and motion-based predictions, which have been proven to be ambiguous. This leads to inaccurate predictions and indirectly deteriorates the performance of the real time applications. This paper performs a detailed review of the existing methodologies, their merits, pitfalls and challenges that create havoc in the video frame prediction process. In addition, this paper performs a detailed analysis on the existing datasets that assist in the video prediction process. This review summarizes various methodologies and datasets along with their performance analysis, which will open research possibilities in the field of video frame prediction. © 2024 IEEE.

关键词： Artificial Intelligence computer Vision Datasets Robotics Video frame prediction

来源：评论

学校读者我要写书评

暂无评论

Identify The Potential Instance of Copy Forgery Using Similar Algorithm 9

Identify The Potential Instance of Copy Forgery Using Simila...

引用

9th International Conference on advanced computing and Communication Systems, ICACCS 2023

作者： Manikandan, A. Kumar, N. Thirumal, S. Vels Institute of Science Technology and Advanced Studies Department of Computer Science and Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350397376

In a similar fashion one of the most popular types of digital art, counterfeit detection necessitates knowledge of picture structures and the ability to generate visual diversions for many purposes, including entertainment. The use of color is very crucial for creating city features. Previous studies have examined the interrelationships of color within homogenous metropolitan zones, looking for connections between neighboring areas and culturally comparable peoples. Color, acclaim, the dissemination of one's color, and satisfaction. When communicating with a foreign audience, it is common practice to have the message reviewed and edited to conform to the local language and cultural norms. © 2023 IEEE.

关键词： Color

来源：评论

学校读者我要写书评

暂无评论

Artificial Intelligence in Health Care computing and Assessments in Oman: an Effectual Study 2

Artificial Intelligence in Health Care Computing and Assessm...

引用

2nd International Conference on Machine Learning and Autonomous Systems, ICMLAS 2025

作者： Wilfred Blessing, N.R. Gunasekaran, Hemalatha Hariharan, B. Jabri, Jaber Saleh Salim Al Kavitha, S.J. Sutherlin Subitha, G. College of Computing and Information Sciences University of Technology and Applied Sciences Ibri Oman SRM Institute of Science and Technology Department of Computational Intelligence Tamil Nadu Kattankulathur India Vels Institute of Science Technology and Advanced Studies Department of Computer Science and Engineering Chennai India Stella Mary's College of Engineering Department of Computer Science and Engineering Tamil Nadu Aruthenganvilai India

ISBN: (纸本)9798331505745

Health care plays a vital responsibility in a human life span. World countries targets to provide better care for their citizens. Digital transformations and innovations in Artificial Intelligence (AI) technologies helps in deep for the novel solutions to speed-up the decision making process in health management and patient consulting. AI branches including Machine Learning (ML), Deep Learning (DL), Neural Networks (NN), Natural Language Processing (NLP) and so forth can support innovations in heal care domain. This paper presents the comprehensive and noble review on recent existing tools and techniques and also recommends advanced techniques for health care industry that are to be used in Sultanate of Oman. Furthermore, overcoming AI challenges are resulted and presented through the study. This work mainly aimed to produce the multiple dimensions and challenges that helps to develop AI powered real-life applications in health care support system. © 2025 IEEE.

关键词： Nutrition

来源：评论

学校读者我要写书评

暂无评论

Generalizations across filler-gap dependencies in neural language models 28

Generalizations across filler-gap dependencies in neural lan...

引用

28th Conference on Computational Natural Language Learning, CoNLL 2024

作者： Howitt, Katherine Nair, Sathvik Dods, Allison Hopkins, Robert Melvin Department of Linguistics University of Maryland United States Department of Computer Science University of Maryland United States University of Maryland Institute for Advanced Computer Studies United States

ISBN: (纸本)9798891761780

Humans develop their grammars by making structural generalizations from finite input. We ask how filler-gap dependencies, which share a structural generalization despite diverse surface forms, might arise from the input. We explicitly control the input to a neural language model (NLM) to uncover whether the model posits a shared representation for filler-gap dependencies. We show that while NLMs do have success differentiating grammatical from ungrammatical filler-gap dependencies, they rely on superficial properties of the input, rather than on a shared generalization. Our work highlights the need for specific linguistic inductive biases to model language acquisition. © 2024 Association for Computational Linguistics.

关键词： Modeling languages

来源：评论

学校读者我要写书评

暂无评论

Exploring The Socio-Cognitive Determinants of Antibiotic Compliance: The Mediating Role of Antimicrobial Resistance Awareness

Exploring The Socio-Cognitive Determinants of Antibiotic Com...

引用

International Conference on Inventive Computation Technologies (ICICT)

作者： Fathima Rumaiza S. Kamalakkannan Department of Computer Science School of Computing Sciences Vels Institute of Science Technology and Advanced Studies Pallavarm Chennai India Department of Computer Applications School of Computing Sciences Vels Institute of Science Technology and Advanced Studies Pallavaram Chennai India

ISBN: (数字)9798331512248

ISBN: (纸本)9798331512255

Antimicrobial resistance (AMR) is a meaningful and growing public health concern that is largely driven by improper antibiotic use. An important factor contributing to AMR is the failure to complete prescribed antibiotic courses, which allows resistant bacteria to survive as well as spread. This study examines the effect of awareness of AMR on the likelihood that people will adhere to their prescribed antibiotic regimens. Using a chi-square test for independence, the analysis identifies a statistically meaningful association between AMR awareness and the completion of antibiotic courses. Results indicate that people who are aware of AMR and its risks are more likely to complete their prescribed courses than those with lower awareness levels. The study explores several factors influencing adherence, including personal health beliefs, access to adequate medical advice and common misconceptions about antibiotic use, along with this key finding. Many people discontinue antibiotics after symptoms subside, completely unaware of the meaningful risks linked with incomplete treatment. Effectively dealing with these issues is important for considerably reducing the spread of AMR. The study suggests multiple public health interventions to improve antibiotic compliance, which include educational campaigns, increased patient counseling and stricter prescription guidelines. These strategies can considerably help curb the rising threat of AMR by importantly increasing awareness and promoting responsible antibiotic use.

关键词： Employee welfare Antibiotics Bacteria Public healthcare Immune system Guidelines

来源：评论

学校读者我要写书评

暂无评论

A Comparative Study on the Application of Text Mining in Cybersecurity

引用

Recent Advances in computer science and Communications 2023年第3期16卷 80-93页

作者： Barik, Kousik Misra, Sanjay Konar, Karabi Kaushik, Manju Ahuja, Ravin Department of Computer Science JIS Institute of Advanced Studies & Research JIS University Kolkata India Department of Computer Science and Communication Ostfold University Halden Norway Department of Computer Engineering Amity University Jaipur India Center of ICT/ICE Research CUCRID Covenant University Ota Nigeria

Aims: This paper aims to conduct a Systematic Literature Review (SLR) of the relative applications of text mining in cybersecurity. Objectives: The amount of data generated worldwide has been attributed to a change in different activities associated with cyber security, and demands a high automation level. Methods: In the cyber security domain, text mining is an alternative for improving the usefulness of various activities that entail unstructured data. This study searched databases of 516 papers from 2015 to 2021. Out of which, 75 papers are selected for analysis. A detailed evaluation of the selected studies employs sources, techniques, and information extraction on cyber security applications. Results: This study extends gaps for future studies, such as text processing, availability of datasets, innovative methods, and intelligent text mining. Conclusion: This study concludes with interesting findings of employing text mining in cybersecurity applications;the researchers need to exploit all related techniques and algorithms in text mining to detect and protect the organization from Cybersecurity applications. © 2023 Bentham science Publishers.

关键词： Data mining

来源：评论

学校读者我要写书评

暂无评论

Multi-criteria rating conversion without relation loss for recommender systems

引用

International Journal of computers and Applications 2022年第2期44卷 130-138页

作者： Sitkrongwong, Padipat Maneeroj, Saranya Takasu, Atsuhiro Department of Informatics School of Multidisciplinary Sciences The Graduate University for Advanced Studies SOKENDAI Tokyo Japan Advanced Virtual and Intelligent Computing Center Department of Mathematics and Computer Science Faculty of Science Chulalongkorn University Bangkok Thailand National Institute of Informatics Tokyo Japan

Traditional recommender systems let users provide a single rating indicating their overall preferences toward items. Beside overall rating, multi-criteria recommender systems let users rate on multiple aspects of items with multi-criteria ratings. Most methods in recommender systems are based on collaborative filtering, which makes recommendations by exploiting ratings from neighbor users. However, most of them ignore the fact that rating behaviors of users vary due to their personal preference biases. Thus, exploiting ratings from neighbors directly might result in a poor recommendation. To solve this, the rating conversion techniques have been applied in some single criterion recommendations. For multi-criteria ratings, converting each criterion rating independently might result in loss of relation among criteria ratings. We propose a novel method that simultaneously converts all criteria ratings between users to maintain their implicit relations. The multi-criteria ratings are first normalized by variances of users and principle component analysis is applied to extract user preference patterns. Such patterns are then used for multi-criteria rating conversion. The experiment results show that our method outperforms both current single and multi-criteria rating conversion techniques with RMSEs of 1.1082 and 3.5574 on TripAdvisor and Yahoo datasets respectively, while maintaining considerably high level of prediction coverages. © 2019 Informa UK Limited, trading as Taylor & Francis Group.

关键词： Recommender systems

来源：评论

学校读者我要写书评

暂无评论

Segmentation of Skin Lesion Image Using FCM with Color Transformation Saliency 1

Segmentation of Skin Lesion Image Using FCM with Color Trans...

引用

1st IEEE International Conference on computing and Data science, ICCDS 2024

作者： Bavya, S. Saravana Kumar, V. Kavitha, M. Anantha SivaPrakasam, S. Vels Institute of Science Technology & Advanced Studies Department of Computer Science & Engineering Chennai India Sreenidhi Institute of Science and Technology Department of Information Technology Hyderabad India S A Engineering College Department of Computer Science & Engineering Chennai India Rajalakshmi Engineering College Department of Computer Science & Technology Chennai India

ISBN: (数字)9798350365337

ISBN: (纸本)9798350365337

In the majority of Western nations including America, Australia and Europe, skin cancer is badly-behaved. Skin concealing, inadequacy of Sun-lights, climate, age, and inherited are major risk factors. Early identification of skin cancer and proceed the treatment can avoid death. The abnormal skin region determines where the skin diseases had been found. Various sorts of skin ailments be existent currently. Melanoma is the sort of skin threat which has grows the greater part of mortality rate. The timely identification and intercession of melanoma include myriad changes of fix. Melanoma has been recognized by shape, size, concealing and outward of the skin injury. This paper demonstration about the traditional clustering technique in particular Fuzzy Clustering technique is acted in these skin lesion pictures. This strategy is segmenting this melanoma from these dermoscopic images effectively. The presentation of this strategy is assessed as far as pixel grouped and time complexity. © 2024 IEEE.

关键词： Feature extraction

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：