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A Survey of Vision-based Fire Detection using Convolutional Neural Networks 4

A Survey of Vision-based Fire Detection using Convolutional ...

引用

4th international conference on Big Data engineering and Education, BDEE 2024

作者： Chen, Gong-Suo Chandarasupsang, Tirapot Luo, Xiao-Dong Tananchana, Annop Mu, Lei International College of Digital Innovation Chiang Mai University Chaing Mai Thailand School of Information and Engineering Sichuan Tourism University Chengdu China School of Information and Engineering Chengdu University Chengdu China

ISBN: (纸本)9798350388268

Fire can harm humans and animals and destroy the natural environment. Early and accurate fire detection is crucial. However, detecting fire is very challenging due to its varying color, size, shape, texture, and the uncertainty of different environments. In this paper, we review literature on datasets, attention mechanisms, and networks, which are the most important components of a fire detection model. We first present key notations to describe the network structure and its key components. then, we introduce several attention mechanisms to reduce the false alarm rate. After that, we present numerous state-of-the-art neural networks for fire, flame, and smoke detection. Finally, we discuss several challenges and opportunities at the end of this paper. © 2024 IEEE.

关键词： Premixed flames

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Conversational Chatbot Builder - Smarter Virtual Assistance with Domain Specific AI 4

Conversational Chatbot Builder - Smarter Virtual Assistance ...

引用

4th international conference for Emerging Technology, INCET 2023

作者： Nandini Prasad, K.S. Sudhanva, S. Tarun, T.N. Yuvraaj, Yuvraaj Vishal, D.A. Dayananda Sagar Academy of Technology and Management Department of Information Science Engineering Bangalore India

ISBN: (纸本)9798350335750

artificial intelligence (AI) has the potential to revolutionize the healthcare industry by providing efficient and accurate medical assistance to patients and healthcare professionals. In this literature survey paper, the focus is on the use of Generative Pretrained Transformer (GPT) technology in developing medical consultant chatbots. the objective is to demonstrate the potential for AI-powered chatbots to improve the efficiency and accuracy of medical assistance. the paper provides an overview of the current state of the art medical chatbots, the challenges and limitations of using GPT for medical consultation and insights into future directions for the development of these chatbots are also discussed. Finally, the paper concludes with a discussion of the potential benefits of using GPT-based medical consultant chatbots in providing accessible and efficient health information to patients. © 2023 IEEE.

关键词： artificial intelligence

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Application Of Genetic programming Algorithm in Flow Control 4

Application Of Genetic Programming Algorithm in Flow Control

引用

4th international conference on artificial Intelligence and Electromechanical Automation, AIEA 2023

作者： Sun, Jiyuan International College of Engineering Changsha University of Science & Technology Changsha410000 China

ISBN: (纸本)9781510666412

As a major discipline in the field of fluid mechanics, flow control is commonly used in academic research and engineering applications. However, because the flow problem is more complex as a nonlinear problem, it has been very difficult to carry out closed-loop control in its research process. Machine learning has developed rapidly in recent years, where genetic programming provides an optimization method for solving flow control problems. this paper reviews the successful cases of combining genetic planning with flow control in the experimental field by showing the application methods of genetic planning and flow control, and analyzes the advantages and disadvantages of genetic planning in flow control applications. the article describes the overall overview of the application of genetic programming in flow control, but because the application of genetic programming in flow control is still in its infancy, through this paper we also hope to promote the application of genetic programming in the field of flow control engineering. © 2023 SPIE.

关键词： Genetic programming

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Research on Digital Signal Denoising Techniques Based on Convolutional Neural Networks 4

Research on Digital Signal Denoising Techniques Based on Con...

引用

4th international conference on Electronic Information engineering and Computer Technology, EIECT 2024

作者： Liu, Xingyu Jiang, Yunsheng Wang, Haolin Liu, Kun College of Intelligent Equipment Shandong University of Science and Technology Tai'an China

ISBN: (纸本)9798331528850

In recent years, convolutional neural networks (CNNs) have demonstrated considerable potential in the domain of digital signal denoising, effectively overcoming the constraints of conventional filtering and spectral methodologies. Digital signals are frequently subjected to a variety of noise interferences, which not only impair the signal quality but also introduce errors in the data. In this work, we propose a novel multi-level convolutional neural network (CNN) denoising architecture that combines residual learning and an attention mechanism to selectively amplify key features while removing noise. the model structure incorporates a dual transformation of the time domain and the frequency domain, enabling the capture of complex dependencies in diverse noise patterns through the use of dilated convolution and adaptive jump connection. Furthermore, a multi-scale feature fusion strategy has been devised with the objective of enhancing the denoising performance of the model at varying noise levels, thereby improving its robustness to different signal-to-noise ratios. the experimental results demonstrate that the proposed method exhibits a notable superiority over the current state-of-the-art denoising techniques in terms of signal fidelity and detail preservation. Furthermore, it is evident that the method is adaptable to a diverse range of noise scenarios. © 2024 IEEE.

关键词： Convolutional neural networks

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A Review of Advancements in Driver Emotion Detection: Deep Learning Approaches and Dataset Analysis 4

A Review of Advancements in Driver Emotion Detection: Deep L...

引用

4th international conference on Innovative Research in Applied science, engineering and Technology, IRASET 2024

作者： Alfaras, Mohammed Shukur Karan, Oǧuz Altinbas University Electrical And Computer Engineering Istanbul Turkey

ISBN: (纸本)9798350309508

this review paper delves into the rapidly evolving field of driver emotion detection, with a specific focus on the contributions of deep learning methodologies and the diverse datasets that facilitate this research. Facial emotion detection and recognition is a highly dynamic and challenging field in Machine Learning (ML) and artificial Intelligence (AI). It has gained attraction for several decades, but it is extremely challenging due to the intrinsic complexities associated with understanding and interpreting human emotions. Understanding and responding to a driver's emotions is increasingly important when autonomous or assisted driving becomes common. To ensure safety, comfort, and optimal interaction between the driver and the car's systems, predicting the emotional state of the driver is essential, also of great significance in practical applications. We give a comprehensive survey of the state-of-the-art driver emotion recognition works that can effectively make use of the recent deep-learning approaches to identify complex emotional cues. Moreover, we explain a variety of datasets that play a vital role in flourishing this field along with the analysis of their effect, like AffectNet, CK+, and EMOTIC. Via this survey we try to investigate the challenges authors are faced with involving this field, e.g., concerns about data privacy, real-time processing demands, and the need for interdisciplinary collaboration. More importantly, the potential of these technologies to improve the driving experience and road safety has been highlighted. We hope this survey can benefit researchers and practitioners to have more insights and provide directions for advancing drivers' emotions. © 2024 IEEE.

关键词： Emotion Recognition

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A Well Structured Design for Individualized Healthcare System via Fuzzy Logic System (FLS) 4

A Well Structured Design for Individualized Healthcare Syste...

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4th IEEE international conference on Advance Computing and Innovative Technologies in engineering, ICACITE 2024

作者： Raman, Ramakrishnan Verma, Apurv Kumar, Vikram Rastogi, Shailesh Pillai, Biju G. Meenakshi, R. India Parul Institute of Technology Parul University Computer Science and Engineering Faculty of Engineering and Technology India Srv Media Pvt. Ltd India Pune India Faculty of Management It & Business Analytics India Institute of Technology Computer Science and Engineering Chennai India

ISBN: (纸本)9798350360165

Personalized medicine is driving the need for new and customized biopharmaceuticals using proteins that have been changed. As such, it is critical to evaluate these items for allergenicity before introducing them as treatments. Even though there are a number of techniques available to predict the allergenicity of proteins, it may still be difficult to discriminate between allergens and nonallergens, particularly when the allergens have a considerable sequence resemblance to their known counterparts. To address this, we provide 'FuzzyApp,' a novel fuzzy rule-based system that evaluates a query protein's potential for allergenicity. FuzzyApp uses fuzzy IF-thEN rules that come from five different modules to determine how allergenic a protein is. FuzzyApp outperforms the state-of-the-art techniques on a variety of datasets, attaining a pleasing trade-off between specificity and sensitivity, as shown by an upbeat Mathew's correlate coefficient. FuzzyApp's capacity to distinguish allergens from allergen-like potential nonallergens (APN) is highlighted by its notable high specificity in this regard. the efficacy and uniformity of this suggested approach are further supported by error analysis and analysis of the whole proteome dataset. Furthermore, Tropomyosin from a variety of allergic and nonallergenic sources is properly predicted by FuzzyApp. the companion online service helps users comprehend the reasoning behind predictions by facilitating batch sequence filing and presenting findings in coherent words. © 2024 IEEE.

关键词： Personalized medicine

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Disturbance rejection of interconnected positive systems 4

Disturbance rejection of interconnected positive systems

引用

2023 4th international conference on Electrical Technology and Automatic Control, ICETAC 2023

作者： Guo, Yu Xu, Shengyuan Du, Baozhu School of Automation Nanjing University of Science and Technology Jiangsu Nanjing210094 China School of Information and Communication Engineering Hainan University Hainan Haikou570228 China

this paper investigates the issue of stability of interconnected systems, where the systems are composed of perturbed positive subsystems and a interconnection matrix. To address the challenge posed by disturbances, a disturbance observer is formulated for disturbance estimation. the estimated disturbance is incorporated into the input of a controller, which is crafted to produce control inputs reliant on both the system state and the estimated disturbance. Using linear copositive functions, a controller design methodology based on linear programming is established. Ultimately, the efficacy of the proposed approach is substantiated through the illustration of numerical example. © Published under licence by IOP Publishing Ltd.

关键词： Disturbance rejection

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Bridging Traditional and AI Methods: A Novel Approach to Breast Cancer Prediction 4

Bridging Traditional and AI Methods: A Novel Approach to Bre...

引用

4th international conference on Advancement in Electronics and Communication engineering, AECE 2024

作者： Kumar, Aditya Gill, Kanwarpartap Singh Kumar, Mukesh Rawat, Ruchira Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Graphic Era Hill University Computer Science & Engineering Uttarakhand Dehradun248002 India Graphic Era Deemed to Be University Computer Science & Engineering Uttarakhand Dehradun248002 India

ISBN: (纸本)9798350364729

Cancer ranks as the second leading cause of death worldwide, with 8.8 million fatalities attributed to it in 2015. Among women, breast cancer is the foremost cause of mortality. Numerous studies have been conducted to identify breast cancer at an early stage, which is critical for initiating treatment and improving survival rates. Breast cancer is a complex disease characterized by various types and forms. It uniquely affects women globally and can often result in death. the primary objective of this paper is to develop a predictive model for breast cancer using different machine learning techniques. It will also evaluate and compare the performance of various classifiers based on metrics such as recall, accuracy, precision, F1-score, and support. We propose employing a machine learning approach to identify patients with triple-negative breast cancer by analyzing their gene expression data. Researchers in machine learning have been experimenting with different methods to enhance outcomes, particularly focusing on accurately classifying samples from the larger population while giving less emphasis to those from smaller groups. Machine learning refers to the process of teaching computers to learn and perform tasks independently, without explicit programming or instructions. In this context, the data is utilized to estimate the likelihood of developing breast cancer. this article also includes the data used for the diagnosis and detection of breast cancer. the proposed model is capable of utilizing various types of information, including imaging and blood samples. the findings illustrate the potential of machine learning to effectively distinguish between triple-negative breast cancer and other cancer types. © 2024 IEEE.

关键词： Lung cancer

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An Immersive Ceramic Display and Personalized Decoration Method Based on WebVR 4

An Immersive Ceramic Display and Personalized Decoration Met...

引用

4th international conference on artificial Intelligence, Virtual Reality and Visualization, AIVRV 2024

作者： Peng, Yongkang Yang, Shixiong Liao, Shuhong School of Information Engineering Jingdezhen Ceramic University Jiangxi China

ISBN: (纸本)9798331528744

With the advent of the digital age, virtual ceramic display platforms have emerged, utilizing virtual reality technology to break geographical boundaries, allowing ceramic enthusiasts from around the world to appreciate and explore the art of ceramics in an immersive environment. Existing virtual display platforms are primarily limited to applying texture maps on preset blank ceramic models, lacking simulation of the diversity and complexity of real ceramics. this paper proposes a virtual display and decoration method for ceramic products based on WebVR, featuring two major functions: virtual display of ceramic products and virtual decoration. through the method of updating decorative textures of ceramic products, it realizes virtual decoration based on the virtual display of ceramic products, which not only breaks the spatial and temporal limitations of ceramic product display and compensates for the fragility of ceramic products, but also provides users with a highly personalized experience, offering ceramic enthusiasts an information-based solution to truly feel the charm of ceramic art in a virtual environment. © 2024 IEEE.

关键词： Virtual environments

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Efficiency Measurement of k-Partitioning of Mobile WSN 4

Efficiency Measurement of k-Partitioning of Mobile WSN

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4th IEEE international conference on Computing, Communication, and Intelligent Systems, ICCCIS 2023

作者： Hossain, Azad Rehena, Zeenat Murshidabad Institute of Technology Lecturer in Computer Science and Technology Berhampore India Aliah University Dept. of Computer Science and Engineering Kolkata India

ISBN: (纸本)9798350306118

Network partitioning improves the energy efficiency of the network. In this work, the algorithm (KP-MWSN) can determine the no. of partitions (k) required based on the delay tolerance limit of each node of MWSN. It can be fruitful for the events where a small amount of delay can be accepted but efficiency has not been calculated in respect of a metric. So, we have measured the efficiency of KP-MWSN algorithm and the results are compared with the Topology Partitioning Scheme (TPS). the simulation result shows that in every randomly created event the efficiency of KP-MWSN is always better than other related state-of-the-art work. © 2023 IEEE.

关键词： Energy efficiency

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