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检索条件"任意字段=5th Conference on Applications and Science of Computational Intelligence"

共 5997 条记录，以下是1-10 订阅

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A Comprehensive Survey on Enhancing Patient Care through Deep Learning and IoT-Enabled Healthcare Innovations 5th

A Comprehensive Survey on Enhancing Patient Care Through Dee...

引用

5th International conference on Data science, Machine Learning and applications

作者： Valaboju, Sabitha Devi, T. Rupa Devi, D. Gayathri Sudheer, P. CVR Coll Engn Hyderabad Telangana India Keshav Mem Inst Technol Hyderabad Telangana India Vignan Bharathi Inst Technol Hyderabad Telangana India

ISBN: (纸本)9789819780334;9789819780310;9789819780303

this study explores recent transformative advancements in deep learning-based healthcare technologies, revolutionizing patient care by enabling personalized precision medicine and extending access through IoT and cyberphysical systems. Diagnostic methodologies for critical conditions like cancer, diabetes, and heart failure are examined, utilizing computational intelligence to enhance patient identification and treatment. the focus lies on electronic health records (EHRs), investigating contemporary deep learning techniques for cancer prediction and framework-based mechanisms for healthcare optimization. Key algorithms like SVMs, Autoencoders, and CNNs are explored, showing applicability in clinical settings and genomic sequence-based diagnostics. Healthcare's unique processing techniques, spanning gene-based strategies, clinical tests, observation, and diagnostic models, are scrutinized for predictive and treatment potential. Integration of statistical and medical references is highlighted for efficient predictions alongside patient-specific data. the research advocates for AI-powered DSS integration, with CNNs as potent tools for customized medical interventions, marking a significant step towards elevated patient care and precision medicine realization.

关键词： Deep learning IoT-driven Healthcare Innovations Electronic Health Records (HER) computational intelligence

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Effective Communication Using Generative AI 5th

Effective Communication Using Generative AI

引用

5th International conference on Data science, Machine Learning and applications

作者： Hegde, Nagaratna P. Vikkurty, Sireesha Sriperambuduri, Vinay Kumar Srikanth, Bingi Rao, Kakumanu BalaSubba Vasavi Coll Engn Dept CSE Hyderabad Telangana India

ISBN: (纸本)9789819780334;9789819780310;9789819780303

Artificial intelligence (AI) has experienced substantial progress in recent times, resulting in the birth of ChatGPT, a cutting-edge conversational AI model. Fuelled by advanced learning techniques and natural language processing (NLP), ChatGPT has completely altered the way humans engage with machines. this research document presents a thorough examination of ChatGPT, delving into its framework, training approach, uses, and moral concerns. Additionally, it spotlights the potential obstacles and forthcoming directions for enhancing ChatGPT's capabilities [1], with the aim of achieving even more authentic and dependable conversational interactions.

关键词： ChatGPT Artificial intelligence Prompt Data Set Transformer Model OpenAI

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Generative AI in Arabic Music: Composition and Innovation 5

Generative AI in Arabic Music: Composition and Innovation

引用

5th IEEE Middle East and North Africa COMMunications conference, MENACOMM 2025

作者： Anaie, Shireen Safatly, Lise Department of Computer Science and IT Kaslik Lebanon

ISBN: (纸本)9798331519957

this paper explores the power of artificial intelligence in the generation of Arabic music, a domain where traditional musical complexity meets modern computational techniques. It focuses on pulling Long Short-Term Memory (LSTM) networks and Convolutional Neural Networks (CNNs) to model and generate music sequences that maintain the distinctive qualities of traditional Arabic compositions. Utilizing a unique dataset of MIDI files from iconic Arabic songs, the study aims to demonstrate the capabilities of AI in understanding and reproducing the complex patterns of Arabic music. this research not only contributes to the academic field by filling the gap in studies concerning Arabic music generation but also enhances practical applications by providing tools that enable non-experts to produce music autonomously. © 2025 IEEE.

关键词： Convolutional neural networks

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Design and Development of Traffic VANETs for Safety and Accident Avoidance 5th

Design and Development of Traffic VANETs for Safety and Acci...

引用

5th International conference on Data science, Machine Learning and applications

作者： Kadiayla, Ramana Tanam, Aparna Manvita, K. Chaitanya Bharathi Inst Technol Dept Artificial Intelligence & Data Sci Hyderabad 500075 Telangana India G Narayanamma Inst Technol & Sci Dept Informat Technol Hyderabad 500104 Telangana India G Narayanamma Inst Technol & Sci Dept Comp Sci & Technol Hyderabad 500104 Telangana India

ISBN: (纸本)9789819780334;9789819780310;9789819780303

Vehicular ad-hoc networks (VANETs) are one of the recent interests in research industry that have advances in wireless communication and networking models. the ultimate goal of the VANETS is to enable the authorized messaging services towards the vehicles and public networks. To reduce the complexity of the service authorization, it uses proxy vehicles to reduce the complex computational problems. During the authentication of proxy vehicles, it sends multiple messages to frequently get response from the road side units in a more effective way. In the proposed system, proxy based unique authentication scheme is discussed where it cannot provide message authenticity and also it will not resist the mediate attacks. Sometimes, the system accepts the false signatures. Secondly, we proposed a unique identity-based authentication scheme using latest proxy vehicles (ID-MAP). To reconfirm the authentication assurance, the signature is adaptively verified against the chosen message. A robust authentication model is evaluated using the Elliptic Curve discrete Logarithm problem represented as (ECDLP) in the system oracle model.

关键词： Vehicular Ad-hoc Networks Secure Network Wireless Network technologies Safety Accident Avoidance

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Multi-objective Optimization of Antenna Based on Improved WOA-BP Neural Network 5th

Multi-objective Optimization of Antenna Based on Improved WO...

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5th International conference on Neural Computing for Advanced applications (NCAA)

作者： Zhuang, Huawei Sun, Fangzhen Li, Gaoqi Liu, Jianzhao Shandong Jianzhu Univ Sch Informat & Elect Engn Jinan 250101 Peoples R China

ISBN: (纸本)9789819770007;9789819770014

During the design of multi-objective antennas, optimizing efficiency and computing expenses are key considerations. In this essay, a rapid antenna optimization strategy that combines the BP neural network with the non-dominated sorting genetic algorithm II is proposed. Firstly, to enhance the global optimization capability, we improve the whale optimization algorithm by improving population initialization, incorporating a nonlinear convergence factor, and introducing adaptive inertia weights. then, using the IWOA, we optimize the BPNN's initial weights and thresholds to improve model accuracy. Finally, we present a Pareto-optimal three-band antenna optimization, demonstrating that the proposed method can effectively optimize antenna performance while significantly reducing computational cost.

关键词： Antenna optimization BP neural network Improved whale optimization algorithm Pareto-optimal

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Detection of B-ALL Using CNN Model and Deep Learning 5th

Detection of B-ALL Using CNN Model and Deep Learning

引用

5th International conference on Data science, Machine Learning and applications

作者： Dongre, Shital Chindhe, Yash Dabade, Mayur Bondre, Savani Chaudhary, Anannya Vishwakarma Inst Technol Pune Maharashtra India Vishwakarma Inst Technol Dept Artificial Intelligence & Data Sci Pune Maharashtra India

ISBN: (纸本)9789819780334;9789819780310;9789819780303

the detection of B-cell acute lymphoblastic leukemia (B-ALL) plays a crucial role in ensuring timely and effective treatment for patients. Recent advancements in Convolutional Neural Networks (CNNs) and deep learning techniques have shown promise in automating the detection and diagnosis of B-ALL. this project provides a concise overview of the literature surrounding the use of CNN models and deep learning approaches for B-ALL detection. the studies reviewed demonstrate the effectiveness of these techniques in achieving high accuracy and improving the speed of diagnosis. the application of CNN models and deep learning in B-ALL detection has the potential to enhance early identification and improve patient outcomes.

关键词： CNN B-ALL detection deep learning

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Comparative Study of Machine Learning and Deep Learning Techniques for Cancer Disease Detection 5th

Comparative Study of Machine Learning and Deep Learning Tech...

引用

5th International conference on Data science, Machine Learning and applications

作者： Ala, Rajitha Nelson, Leema Jagdish, Muktha Venu, Vasantha Sandhya Chitkara Univ Inst Engn & Technol Rajpura Punjab India Vardhaman Coll Engn Hyderabad India

ISBN: (纸本)9789819780334;9789819780310;9789819780303

Cancer is one of the most dreadful illnesses that plague mankind. the illness has a high mortality rate. there are numerous kinds of this illness. It is challenging to identify these diseases in their early stages. Recent studies have shown the significance of Machine Learning and Deep Learning techniques in disease diagnosis. the most promising methods are presented in this study employing several machine learning and deep learning algorithms and their comparative study to determine the specific type of cancer sickness that a patient has. Additionally, it offers the most effective models for each disease type currently in use analyzed using Accuracy and AUC ROC metrics.

关键词： Cancer Disease detection Machine Learning Deep Learning Artificial intelligence

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Blockchain-based Data Trading Platform for Anti-Resale with Zero-Knowledge Proof and Block-Based Watermarking 24

Blockchain-based Data Trading Platform for Anti-Resale with ...

引用

5th International conference on Computer science and Management Technology, ICCSMT 2024

作者： Hong, Zhicheng School of Artificial Intelligence South China Normal University Guangdong Foshan China

ISBN: (纸本)9798400709999

In blockchain-based data trading platforms, the illegal resale of image data has led to serious copyright infringement *** protective measures typically rely on embedding digital watermarks into images to verify data ownership and ***, to ensure the correctness of the watermark embedding process, the embedded results need to be *** zero-knowledge proof schemes like Groth16 offer efficient verification but are limited in practical applications due to the high computational costs associated with the trusted setup phase required for third-party *** address this issue, this paper proposes a watermark embedding and verification mechanism based on block-based *** partitioning the image and embedding the watermark incrementally, the time required for the trusted setup and zkey generation in zero-knowledge proofs is significantly reduced, thereby improving the overall efficiency of proof *** results show that after partitioning, the total proof generation time is reduced to 24.274% of that in the unpartitioned *** demonstrates that the proposed method significantly reduces proof generation time, making it more efficient for large-scale image data transactions in blockchain environments. © 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Embeddings

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A Comprehensive Exploration of Complex Emotions and their Simplification for Enhancing Sentiment Analysis through Explainable AI 5th

A Comprehensive Exploration of Complex Emotions and Their Si...

引用

5th International conference on Data science, Machine Learning and applications

作者： Sudheer, P. Manoranjini, J. Suman, Naika Reddy, Eedunuri Muralidhar Sridevi, Puligilla CVR Coll Engn Dept CSE AI&ML Hyderabad Telangana India Rajalakshmi Engn Coll Dept Artificial Intelligence & Data Sci Chennai Tamil Nadu India Pallavi Engn Coll Dept CSE DS Hyderabad Telangana India Swami Vivekananda Inst Technol Dept CSE DS Hyderabad Telangana India

ISBN: (纸本)9789819780334;9789819780310;9789819780303

Sentiment analysis plays a pivotal role in comprehending user emotions within the SocialWeb;however, accurately capturing nuanced sentiment remains challenging. Although deep learning models exhibit impressive performance, their lack of transparency and interpretability hinders their real-world applicability. To address this limitation, we propose an Updated SHAP (SHapley Additive exPlanations) method integrated with Explainable Artificial intelligence (XAI) as a solution. the research investigates the potential of XAI in enhancing sentiment analysis by designing, evaluating, and utilizing XAI models. the primary focus is on knowledge discovery, exploring how XAI aids in recognizing, interpreting, and simulating human emotions for sentiment analysis tasks. By illuminating the inner workings of sentiment analysis models, this research aims to substantially improve the reliability and utility of sentiment analysis in socio-affective domains. Emphasizing transparency and trust, XAI fosters informed decision- making and enhances sentiment analysis applications amidst the intricate landscape of user emotions on the Social Web.

关键词： Sentiment analysis AI-driven deep learning transparency Explainable Artificial intelligence (XAI) human emotions prediction accuracy

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Empathetic Conversations in Mental Health: Fine-Tuning LLMs for Supportive AI Interactions 5th

Empathetic Conversations in Mental Health: Fine-Tuning LLMs ...

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5th International conference on Data science, Machine Learning and applications

作者： Mundargi, Zarinabegam Patil, Siddhi Phadke, Mrunmayee Sundkar, Rahul Dongre, Rajkumar Raut, Atharva Vishwakarma Inst Technol Dept Artificial Intelligence & Data Sci Engn Pune 411037 Maharashtra India

ISBN: (纸本)9789819780334;9789819780310;9789819780303

this paper proposes a virtual mental health assistant system to address the neglected yet crucial aspect of mental health. Due to constraints in finance, time, space, and resources for in-person therapy, a virtual assistant can provide continuous attention and conscious efforts to improve mental well-being[1]. the paper explores the potential of generative chatbots in mental health, reviewing the current landscape of mental health services and identifying challenges faced by individuals seeking support. It examines the technologies and functionalities of chatbots, their role in assessment, intervention, and self-management, emphasizing empathetic conversations, tailored interventions, and real-time support[1]. Generative chatbots can enhance mental health support, increase accessibility, reduce stigma, and provide immediate assistance when working alongside human therapists or professionals, empowering individuals on their path to well-being[1].

关键词： Generative Conversational NLP Koala LLM Numpy Pandas LangChain

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