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检索条件"任意字段=2nd International Conference on Pattern Recognition and Machine Intelligence"

共 6962 条记录，以下是21-30 订阅

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Developing an AI-Based Library Assistant: Enhancing Book Retrieval with Natural Language Processing and machine Learning 2

Developing an AI-Based Library Assistant: Enhancing Book Ret...

引用

2nd international conference on Computational intelligence, Communication Technology and Networking, CICTN 2025

作者： Kailash Varma, Nadimpalli Madana Aryan, Adla Dhanush, Pagilla Manikanta, Rangisetti Chandhu, Nalla Arora, Gagan Deep Department of Artificial Intelligence & Machine Learning Vardhaman College of Engineering Telangana Hyderabad501218 India

ISBN: (纸本)9798331530389

The current college library system is hindered by inefficiencies in book searching, availability updates, identity verification, and checkout processes, resulting in delays and errors that negatively impact student experiences. This research paper presents an Al-based librarian system designed to address these challenges through automation and digital transformation. Leveraging a Large Language Model (LLM), the proposed system facilitates personalized interactions between students and library resources. Upon student verification, the AI librarian provides real-time information on book availability, location, and tailored recommendations, significantly reducing the time spent on manual searches. The streamlined checkout process allows for automated book issuance and instant confirmation notifications, minimizing human error and enhancing record- keeping. This innovative solution not only improves operational efficiency but also enriches the user experience by offering a user-friendly interface and timely assistance. Future enhancements, such as voice integration and mobile application support, are suggested to further modernize library services. This research underscores the potential of AI technologies to revolutionize library management and improve service delivery in academic settings. © 2025 IEEE.

关键词： Efficiency

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Research of IT Terminal Behavior Situational Awareness Model Based on Artificial intelligence 24

Research of IT Terminal Behavior Situational Awareness Model...

引用

2nd international conference on Communication Networks and machine Learning, CNML 2024

作者： Wang, Yongqiang Hu, Hong Chen, Yingcong Chen, Zhiming Li, Zilong Meizhou Power Supply Bureau of Guangdong Power Grid Co. Guangdong Meizhou China

ISBN: (纸本)9798400711688

With technological advances and the increasing complexity of the market environment, power grid enterprises need more flexible and comprehensive strategies to optimize current business processes and thus enhance management effectiveness. This thesis aims to propose a set of proven rationalization and verification methods through global and local terminal business process analysis. First, the global terminal behavior link is analyzed by constructing the real terminal behavior link to identify the key business links and potential bottlenecks. Next, in-depth analysis of local terminal behavior links is conducted to identify problems or improvement points in local links. Finally, based on the analysis results, the terminal business process is adjusted and optimized, and the rationality is verified to improve user experience and business efficiency. © 2024 Copyright held by the owner/author(s).

关键词： Endpoint business processes

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LDA-LSTM based on variational entropy weight and multi-dimensional conditional grey association 24

LDA-LSTM based on variational entropy weight and multi-dimen...

引用

2nd international conference on Communication Networks and machine Learning, CNML 2024

作者： Lin, Longxin Fang, Jiahui Yao, Jiaxin Chai, Xiaolong School of Statistics and Mathematics Guangdong University of finance & Economics Guangdong Guangzhou China Institute of Artificial Intelligence and Deep Learning Guangdong University of finance & Economics Guangdong Guangzhou China

ISBN: (纸本)9798400711688

This paper studies the LDA-LSTM model based on variational entropy weight and multidimensional conditional grey relation, and applies it to the actual case of urban traffic congestion in China. Firstly, the paper collects traffic data from 20 cities in China, determines the weight of indicators through variational entropy weight, and innovatively integrates the multidimensional conditional grey relation model to identify the key indicators affecting urban traffic. Then, the paper proposes the LDA-LSTM hybrid model to perform topic analysis on the data, extracts 8 topic words as indicators for LDA-LSTM, and predicts the traffic congestion situation in the first quarter of 2024 in cities, finding that the prediction values fit well and overall achieve good prediction results. © 2024 Copyright held by the owner/author(s).

关键词： Traffic congestion

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Advancing Techniques for Deepfake Detection and Evaluation: Challenges and Innovations 2

Advancing Techniques for Deepfake Detection and Evaluation: ...

引用

2nd international conference on Computational intelligence, Communication Technology and Networking, CICTN 2025

作者： Singh, Pradum Kumar Sharma, Sourav Sachdeva, Ritu School of Computer Applications Manav Rachna International Institute of Research & Studies Faridabad India

ISBN: (纸本)9798331530389

The proliferation of deepfakes-also termed artificial intelligence-generated synthetic media poses unprecedented challenges to the digital authenticity of media, for media integrity, and to societies' trust in its credibility. Despite such significant technological advancements, current methodologies for detecting deepfakes remain somewhat fragmented, reactive, and often unable to keep pace with rapidly evolving technologies in generative AI. This article considers a comprehensive multi-modal approach toward deepfake detection by integrating an advanced machine learning algorithm, novel statistical correlation techniques, and forensic image analysis that would fill in the critical gaps in the existing frameworks. By using an extensive dataset of 10,000 synthetic and authentic media samples from diverse domains, we developed a hybrid neural network architecture that attained 94.3% accuracy on identifying AI-generated content. Our methodology utilized ensemble learning by combining spatial-temporal inconsistency detection, biological signal analysis, and advanced feature extraction algorithms. Key findings demonstrate significant vulnerabilities in current deepfake generation models, with our proposed technique successfully identifying subtle artifacts and inconsistencies across multiple generative AI platforms. This research conclusively demonstrates that proactive, adaptive detection strategies are critical to mitigating the potential risks associated with synthetic media, providing a robust framework for future technological interventions in digital forensics and media authentication. © 2025 IEEE.

关键词： Adversarial machine learning

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IoT-Enabled Smart Classrooms for Enhanced Learning Environments 2

IoT-Enabled Smart Classrooms for Enhanced Learning Environme...

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2nd international conference on Computational intelligence, Communication Technology and Networking, CICTN 2025

作者： Kumar, Prem Negi, Priyanshu Sharma, Priyanka Mittal, Pratham School of Computer Applications Manav Rachna International Institute of Research & Studies Faridabad India

ISBN: (纸本)9798331530389

Innovative integration of digital infrastructure with pedagogical practices in rapidly transforming educational environments. The technology is well recognized yet fails to solve issues in traditional classrooms due to poor resource management, less individualized learning experiences, and real-time performance monitoring. The research focuses on these issues and answers them by designing and implementing an IoT-enabled smart classroom ecosystem aiming at changing the learning environment. Developed an end-to-end IoT framework that incorporates sensor networks, machine learning algorithms, and adaptive learning interfaces across multiple educational institutions using a mixed-method approach. This included prototype development, systematic data collection, and iterative performance analysis using advanced analytics and user experience assessments. Significant learning engagement improvements by 23.7%. Resource usage efficiency improves by 35.2%. Excellent Personalized learning results, Real-time environmental monitoring of the IoT system, Adaptive instructional strategy with the complete track record of the student. The precision control in climate through sensors for an optimum lighting effect Smart management of the space using sensors. In sum, our research establishes a transformative model for technology-enhanced educational spaces, providing a scalable blueprint for future smart learning environments where technological innovation is integrated into pedagogical effectiveness. © 2025 IEEE.

关键词： Adversarial machine learning

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Integrating Artificial intelligence and machine Learning for Folklore Preservation and Innovation 2

Integrating Artificial Intelligence and Machine Learning for...

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2nd international conference on Computational intelligence, Communication Technology and Networking, CICTN 2025

作者： Priyadarshini, Ritupama Goswami, Arpita Vishwakarma, Sarvesh Jain, Paras Gupta, Vishan Kumar Meena, Jaishree School of Liberal Studies KILT Deemed to be University Odisha Bhubaneswar India School of Liberal Studies KIIT Deemed to be University Odisha Bhubaneswar India CSE Department Graphic Era Deemed to be University UK Dehradun India School of Computing Science Engineering and Artificial Intelligence VIT Bhopal University MP Kothrikalan Sehore India Amity School of Engineering and Technology Amity University Punjab Mohali India Department of Bioinformatics Amity School of Biological Sciences Amity University Punjab Mohali India

ISBN: (纸本)9798331530389

In an age where traditional cultures are dealing with the weight of globalization, there is folklore as the means of history, morals and ethics, and societal identity. A diverse oral culture of India that embraces myths, legends, customs and rituals has always been transferred from generation to generation regardless of technological presence. Since the concept of modern technology, particularly Artificial intelligence and ML have come into the limelight, which provides newer dimensions for keeping up and transforming these rich Indian cultures and traditions. The role of AI and ML is preserving and safeguarding Indian folklore by transcribing, cataloging, indexing and analyzing massive collections of vocal cultures. However, AI-based tools like SVM, Random Forest, Decision Tress, Natural Language Processing are considered for their prospective to preserve and protect threatened Indian dialects, as well as AI-based storytelling platforms have initiated creative, vibrant and lively folklore versions. The incorporation of AI in cultural conservation brings several ethical concerns, from probable cultural misrepresentation to the likelihood of homogenizing varied narratives. At the end, this study emphasizes that, if applied with precision, AI can help as a safeguard and as nurturer of folklore, and therefore supports its continuity and significance in a swiftly changing world. © 2025 IEEE.

关键词： Adversarial machine learning

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6th international conference on Computational intelligence in pattern recognition, CIPR 2024

6th International Conference on Computational Intelligence i...

引用

6th international conference on Computational intelligence in pattern recognition, CIPR 2024

ISBN: (纸本)9789819780891

The proceedings contain 45 papers. The special focus in this conference is on Computational intelligence in pattern recognition. The topics include: Vietnamese Text Summarization Using Transformer Approach;DQN Trader: Reinforcement Learning for Automated Trading;indirect Feature Extraction for Efficient Fingerprint recognition;A Novel and Intelligent Neuroimage Analysis for Tumor Classification with Thermo-Color Segmentation Using VGG-16;a Deep Feature Ensemble Methodology for 2D Biomedical Image Classification;detection of Hardware Trojan in Nanocrossbar-Based Cryptographic Circuit;convolutional Neural Network Segmentation for Satellite Imagery Data to Identify Landforms Using U-Net Architecture;performance Comparison of Different machine Learning Classifiers for Diabetes Prediction;Intelligent Anti-tamper Systems: Safeguarding Critical Infrastructure in the Era of Proliferating Interconnected Devices and IoBT;contrasting Various Cryptographic Algorithms for Storage and Cloud Computing Services;A New Technique of Cellular-Automata-Based PUF Design in Nanoscale Crossbar Circuits;CrimeScene2Graph: Generating Scene Graphs from Crime Scene Descriptions Using BERT NER;a Squeeze and Excitation Framework Utilizing ResNet-152 for Alzheimer’s Disease Dementia Classification;Identification of Real or Fake Currency Using Semi-supervised Generative Adversarial Networks (SSGANs);efficient Detection of Fake Twitter Profiles on Social Media Through Hybrid Deep Learning Model;religious Sentiment Analysis and Detection on Social Media;Visualizing NASDAQ Composite Index Historical Data Using Tableau;typeface Identification for English Using Convolutional Neural Networks;Adaptive Ensemble of ML Regressors and LSTM for Stock Price Prediction;PolyNMT: Neural machine Translation Model with Seq2Seq Encoder-Decoder System;a Rectangular Slotted Sierpinski Fractal Bowtie Antenna for Multiband Wireless Communications;enhancing Cardiac Health: machine Learning in Coronary Artery Disease Predi

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Evolution and Future Trends in Wireless Communication: From 2G to 6G Technologies 2

Evolution and Future Trends in Wireless Communication: From ...

引用

2nd international conference on Computational intelligence, Communication Technology and Networking, CICTN 2025

作者： Goel, Deepanshu Jaiwal, Deepanshu Dhruv Chopra, Taruna School of Computer Applications Manav Rachna International Institute of Research & Studies Faridabad India

ISBN: (纸本)9798331530389

The journey from 2G to emerging 6G is impressive, mirroring the long evolutionary path of wireless communication technology. We address critical transitions in cellular networks in light of architectural transformation, performance metrics, and the enablers of new technologies. Key trends identified: from Kbps data rate growth exponentially in 2G to Tbps in 6G;a fall of latency from the 500-ms level to sub-millisecond latency;and more importantly, from human-centric communication to machine-centric communication. It will bring some breakthrough technologies, like terahertz communications, intelligent reflecting surfaces, and quantum computing integration, revolutionizing the network configuration and capability. 6G networks will highlight many unprecedented applications such as holographic communications and extended reality;however, that is not possible without addressing various challenges related to spectrum efficiency, energy optimization, and security challenges. This report synthesized technical literature, standardization documents, and industry insights to propose a roadmap of future wireless networks with innovative and AI-integrated spectrum utilization concepts and sustainable designs. The results are critical to researchers, policymakers, and industry stakeholders in the shaping of the next generation of wireless communication systems. © 2025 IEEE.

关键词： Quantum computers

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Analyzing Sentiments in Twitter Data on Russia-Ukraine Conflict Using machine Learning Methods 2

Analyzing Sentiments in Twitter Data on Russia-Ukraine Confl...

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2nd international conference on Computational intelligence, Communication Technology and Networking, CICTN 2025

作者： Chaudhry, Meeta Kumar, Rakesh Patel, Harvendra Kumar Prakash, Navin Ashish Mishra, D.K. Department of CSIT KIET Group of Institutions Ghaziabad India GNIOT Greater Noida India Noida International University India Department of CSE IIMT College of Engineering Greater Noida India Department of CSE RIMT Bareilly India Department of CSE ABES Ghaziabad India

ISBN: (纸本)9798331530389

As the conflict between Russia and Ukraine has deepened and more international countries have been engaged, it has become critical to ascertain if the universal message is one of support for or opposition to military activities. This goal is supported by research on how public opinion and foreign affairs are critically connected. As a result, researchers looked at how the global community felt about Russia's invasion of Ukraine. In total, 27,894 tweets with the hashtag #UkraineRussia that were published on the first day were examined. The findings indicate that some of the most often recurring words in the tweets were "war," "people," "world," and "people." Sadness was the most prominent emotion, and negative sentiments were higher than positive sentiments. It was discovered that nearly 89% of conflicts involved the word "world" when a term was supervised in context concordance analysis. This finding underlines the rising worry that the situation between Russia and Ukraine may worsen. © 2025 IEEE.

关键词： Tweets

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Research on GSEm-Net detection method of embroidery pattern lightweight operator for digital protection of Gansu intangible cultural heritage Long Embroidery 2

Research on GSEm-Net detection method of embroidery pattern ...

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2nd international conference on Big Data, Computational intelligence, and Applications, BDCIA 2024

作者： Ba, Yuanxiao Lanzhou Vocational Technical College Gansu Lanzhou China

ISBN: (纸本)9781510689053

The digital image of embroidery has complex edge structure and high repetition rate texture features. Post-processing such as region detection is a challenging task. A long embroidery image data set for learning and training is constructed. Based on the deep network and multi-scale detection structure, the lightweight detection network model GSEm-Net is introduced to detect the long embroidery pattern in real time. Experiments show that compared with yoloV8, the detection accuracy of this method is equivalent, and the detection speed is 1.5 times that of yoloV8, but the generated model is smaller, and it is easier to deploy to low-computing edge devices, which effectively improves the target detection efficiency. © 2025 SPIE.

关键词： Convolutional neural networks

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