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检索条件"任意字段=International Conference on Advanced Computer Science Applications and Technologies"

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Proposed Solution for Currency Classification and Fake Currency Detection Using Machine Learning 4

Proposed Solution for Currency Classification and Fake Curre...

引用

4th international conference on Sentiment Analysis and Deep Learning, ICSADL 2025

作者： Narale, Dnyaneshwari. B. Pujar, Anita. M. Pardeshi, K.R. Walchand Institute of Technology Computer Science and Engineering Solapur India

ISBN: (纸本)9798331523923

The rapid advancement of digital technologies has greatly impacted financial systems, creating challenges in accurately classifying currencies and detecting counterfeits in various real-world scenarios. Traditional approaches, such as manual inspections and specialized tools like UV light detectors, tend to be time-consuming, expensive, and less effective against sophisticated counterfeiting methods. Recent developments in machine learning and image processing have shown potential, utilizing supervised machine learning models. Nonetheless, issues remain in managing variations due to wear, folds, inconsistent lighting, and different currency designs. This research introduces a robust machine learning-based system for classifying currencies and detecting counterfeit bills. By combining advanced image processing techniques to extract essential features (like texture, edges, and color histograms) with a hybrid model that integrates CNN, Random Forest, and XGBoost, the proposed framework tackles challenges related to real-world variability and subtle signs of counterfeiting. The goal of the system is to achieve high accuracy and reliability in identifying counterfeit notes while ensuring it can scale and adapt to new counterfeiting methods. © 2025 IEEE.

关键词： Adversarial machine learning

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A Survey on the Landscape of Machine Learning Solutions for Detecting Phishing Attacks 2

A Survey on the Landscape of Machine Learning Solutions for ...

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2nd international conference on Artificial Intelligence, Blockchain, and Internet of Things, AIBThings 2024

作者： Das, Shijon Ibrahem, Mohamed I. Fouda, Mostafa M. Augusta University School of Computer and Cyber Sciences AugustaGA30912 United States Idaho State University Department of Computer Science PocatelloID83209 United States Idaho FallsID United States Idaho State University Department of Electrical and Computer Engineering PocatelloID United States

ISBN: (纸本)9798331529529

Despite the advancements in cybersecurity, phishing attacks continue to pose significant threats to organizations and individuals worldwide. With the advent of time, phishing techniques have become more robust and thus demand more enhanced solutions than the existing ones. This survey paper explores how machine learning (ML) techniques are applied for detecting phishing attacks, offering a comprehensive overview of the challenges faced and the advancements made in the field. The paper discusses the fundamentals of phishing attacks and how ML can be applied to detect those attacks. The paper also discusses the applications of deep learning models and anomaly detection techniques which offer precise results for detecting modern phishing strategies. Finally, this survey addresses the challenges faced by current detection systems and suggests potential areas for future research. The goal of this survey is to provide a comprehensive overview that not only discusses the existing machine learning techniques but at the same time inspires innovation in this domain. © 2024 IEEE.

关键词： Phishing

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Autism Classification Using Machine Learning Techniques 2

Autism Classification Using Machine Learning Techniques

引用

2nd international conference on advanced computer applications, ACA 2023

作者： Altaee, Rasool Alshemari, Raghda M. Kamil, Israa S. Alkhafaji, Buthainah Alazam, Ali Haider Obead, Ola Ali Abdullah, Ammar Abdulhadi Al-mustaqbal University College Medical Laboratories Techniques Department Babil Iraq Al-mustaqbal University College Anesthesia Techniques Department Babil Iraq Al-mustaqbal University College Dentistry Departmeent Babil Iraq Al-mustaqbal University College Medical Physics Department Babil Iraq Shatt Al-Arab University Computer Science Department Basra Iraq

ISBN: (纸本)9798350341829

We are currently seeing a rapid spread of Autism Spectrum Disorder (ASD), so when studying autis0m behaviors, researchers note that this study requires substantial costs and time to characterize autism. Through the use of machine learning techniques, autism can be detected early. There are studies using machine learning techniques, but they have not provided any conclusion in determining the characteristics of autism due to the different ages of people. This study aims is to predict autism in any age group (children, adolescents, adults), using a classification system based on machine learning techniques (random forest (RF), decision tree (CART), Naive Bayes (NB), and Support Vector Machine (SVM). The results from algorithms (CART, SVM, NB, and RF) are evaluated using several metrics (Accuracy, Precision, Recall, F1 Score) based on the AQ dataset- 10. The model used showed advanced results in evaluating the accuracy of the types of datasets. The results provide superior performance for ASD classification. Random Forest and Support Vector Machine accuracy have been improved between (98% and 100%) with features selected by correlation technology and K fold split data. © 2023 IEEE.

关键词： Support vector machines

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A Survey of Legal Text Analysis Techniques for Indian Legal Documents

A Survey of Legal Text Analysis Techniques for Indian Legal ...

引用

2024 international conference on Circuit, Systems and Communication, ICCSC 2024

作者： Ghosh, Trisha Kumar, Shailender Delhi Technological University Computer Science and Engineering Delhi India

ISBN: (纸本)9798350365306

Recent advancements in Natural Language Processing (NLP), particularly transformer-based models, have brought semantically rich word embeddings to the forefront. These innovations hold significant potential for revolutionizing the legal domain by enhancing the analysis and processing of legal documents, thus accelerating justice delivery. In India, with its extensive legal corpus and common law system, implementing NLP technologies presents both challenges and opportunities. The abundance of unstructured data complicates text analysis and information retrieval. This review paper examines the current research landscape, focusing on NLP applications in Indian court case documents. It critically explores progress in areas such as catchphrase identification, court judgment prediction, document summarization, rhetorical role labeling, similarity analysis of court case documents, and legal statute identification. Additionally, it discusses the development of existing language models retrained on Indian legal data to optimize judicial operations, reviewing datasets used and highlighting potential improvements and future research directions. © 2024 IEEE.

关键词： Semantics

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The Controlling of Viability of LM Controller in ULR System 4

The Controlling of Viability of LM Controller in ULR System

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4th IEEE international conference on Advance Computing and Innovative technologies in Engineering, ICACITE 2024

作者： Mukesh Singh, Kamreed Udham Jabbar, Kadim A. Sathish Kumar, M. Hussein, Laith Abdtawfeeq, Tareq Hafdhi Jaafar, Abdul Hassan Majli Alwan, Ali Saad Hindustan Institute of Technology and Science Department of Computer Applications India Graphic Era Hill University School of Computing uttarakhand Dehradun248007 India Graphic Era Deemed to Be University uttarakhand Dehradun248007 India National University of Science and Technology College of Technical Engineering Dhi qar64001 Iraq The Islamic University College of Technical Engineering Department of Computers Techniques Engineering Najaf Iraq Al-farahidi University Baghdad Iraq Al-kunooze University College Medical Instrument Department Basra Iraq Kut University College Business Administration Department wasit Al Kut52001 Iraq

ISBN: (纸本)9798350360165

The Leap Motion Controller is an affordable marker-less optical sensor that uses a range of characteristics to follow the movements of the human hand. Individuals with disabilities are the focus of upper limb rehabilitation treatment, which uses continuous motion exercises to promote healing. However, patients' motivation may be impacted by the repeated nature of these activities, which might be viewed as boring or demoralising. Serious games have been included into therapy to improve motivation and enjoyment in order to address this. This study looks at the feasibility, repeatability, and accuracy of using a Leap Motion Controller (LMC) in conjunction with a serious game to aid with upper limb rehabilitation. The results of experimental feasibility tests, which recreate upper limb motions detected by the LMC using an industrial robot, show good tracking accuracy. On the other hand, noted restrictions concerning quantifiable workplace are addressed.. © 2024 IEEE.

关键词： Industrial robots

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Enhancing IoT Networking Through Predictive Big Data Processing 2

Enhancing IoT Networking Through Predictive Big Data Process...

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2nd international conference on Artificial Intelligence and Machine Learning applications, AIMLA 2024

作者： Jain, Sandeep Kumar Hannah Jessie Rani, R. Paikaray, Divya Vivekananda Global University Department of Electrical Engineering Jaipur India School of Engineering and Technology Department of Electrical and Electronics Engineering Karnataka Bangalore India ARKA JAIN University Department of Computer Science & IT Jharkhand Jamshedpur India

ISBN: (纸本)9798350349221

the net of things (IoT) promises to revolutionize the way humans interact with their surroundings. Notwithstanding this promise, the deployment of IoT networks is hindered by using several challenges, particularly related to communication, scalability, and electricity performance. This paper proposes a technique to address those demanding situations through predictive big statistics processing blended with the use of new network technology. In particular, the use of prediction fashions, system studying, and analytics algorithms will permit IoT networks to investigate past and present facts in order to forecast destiny traits. Additionally, the use of latest and existing network technologies, which include extremely-low strength mesh networks, 5G, and electricity-conscious network routing protocols will help to improve the overall performance of IoT networks. In conclusion, this paper gives a method to decorate the characteristic of IoT networks through predictive big statistics processing as a way to permit more effective, efficient, and reliable communique for all related devices. © 2024 IEEE.

关键词： Scalability

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Advancing Brain Image Segmentation: A Comprehensive Exploration of Enhanced VGG16 Architecture for Precise Neuroanatomical Mapping 2

Advancing Brain Image Segmentation: A Comprehensive Explorat...

引用

2nd international conference on Computing and Data Analytics, ICCDA 2024

作者： Sheeja Kumari, V. Wilfred Blessing, N.R. Palarimath, Suresh Gunasekaran, Hemalatha Poorana Senthilkumar, S. Sutherlin Subitha, G. Saveetha School of Engineering Simats University Department of Computational Intelligence Chennai600 025 India College of Computing and Information Sciences University of Technology and Applied Sciences Ibri Oman College of Computing and Information Sciences University of Technology and Applied Sciences Salalah Oman Dr. N. G. P Arts and Science College Department of Computer Applications Tamil Nadu Coimbatore India Stella Mary's College of Engineering Department of Computer Science and Engineering Tamil Nadu Kanyakumari India

ISBN: (纸本)9798331542573

This study introduces a novel approach to brain image segmentation by enhancing the VGG16 architecture. Neuroanatomical mapping is a critical aspect of understanding brain structures, and our research focuses on refining the VGG16 model to achieve more accurate segmentation results. We address the intricacies of brain image analysis, optimizing the architecture for the nuanced structures inherent in neuroimaging data. Our enhanced VGG16 model is thoroughly evaluated across diverse datasets, demonstrating superior performance compared to state-of-the-art segmentation methods. The framework proves robust and efficient in accurately delineating complex brain regions. We also delve into the interpretability of the segmentation results, shedding light on the learned features that contribute to the model's efficacy. The significance of our work extends beyond improved segmentation, offering valuable insights into the interpretability of deep learning models in neuroimaging. This research contributes to the broader field of biomedical image analysis and holds promise for applications in neuroscience and medical diagnostics. The proposed enhanced VGG16 framework emerges as a potent tool for advancing our understanding of brain structures and enhancing the capabilities of neuroimaging technologies. © 2024 IEEE.

关键词： Brain mapping

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Deepfakes, Misinformation, and Disinformation in the Era of Frontier AI, Generative AI, and Large AI Models 5

Deepfakes, Misinformation, and Disinformation in the Era of ...

引用

5th international conference on computer and applications, ICCA 2023

作者： Shoaib, Mohamed R. Wang, Zefan Ahvanooey, Milad Taleby Zhao, Jun Nanyang Technological University School of Computer Science and Engineering Singapore

ISBN: (纸本)9798350303254

With the advent of sophisticated artificial intelligence (AI) technologies, the proliferation of deepfakes and the spread of m/disinformation have emerged as formidable threats to the integrity of information ecosystems worldwide. This paper provides an overview of the current literature. Within the frontier AI's crucial application in developing defense mechanisms for detecting deepfakes, we highlight the mechanisms through which generative AI based on large models (LM-based GenAI) craft seemingly convincing yet fabricated contents. We explore the multifaceted implications of LM-based GenAI on society, politics, and individual privacy violations, underscoring the urgent need for robust defense strategies. To address these challenges, in this study, we introduce an integrated framework that combines advanced detection algorithms, cross-platform collaboration, and policy-driven initiatives to mitigate the risks associated with AI-Generated Content (AIGC). By leveraging multi-modal analysis, digital watermarking, and machine learning-based authentication techniques, we propose a defense mechanism adaptable to AI capabilities of ever-evolving nature. Furthermore, the paper advocates for a global consensus on the ethical usage of GenAI and implementing cyber-wellness educational programs to enhance public awareness and resilience against m/disinformation. Our findings suggest that a proactive and collaborative approach involving technological innovation and regulatory oversight is essential for safeguarding netizens while interacting with cyberspace against the insidious effects of deepfakes and GenAI-enabled m/disinformation campaigns. © 2023 IEEE.

关键词： Artificial intelligence

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Multi-label Classification Model for Consumer Product Defect Clues Based on BERT-GCN 4

Multi-label Classification Model for Consumer Product Defect...

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4th international conference on Advances in Electrical Engineering and computer applications, AEECA 2023

作者： Tian, Jingjing Lv, Xueqiang Feng, Xinhao China National Institute of Standardization Beijing100191 China Beijing Information Science & Technology University Beijing100191 China

ISBN: (纸本)9798350308082

Multi-label text classification is one of the important subtasks in the field of natural language processing. Multi-label classification of consumer product defect clues is the foundation for conducting multi-source data association analysis. This paper proposes a multi-label classification model for defect clues that integrates BERT (BidirectionalEncoder Representations from Transformer) and GCN (Graph Convolution Network) to address the labeling problem of consumer product defect clues. The model is compared and tested based on 10351 historical case data. The experimental results show that the accuracy of the multi-label intelligent classification model reaches higher than 65%, which can effectively improve the efficiency of defect clue analysis. © 2023 IEEE.

关键词： Defects

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Prediction of thermal parameters for flat plate solar water heater by machine learning - A Review 6

Prediction of thermal parameters for flat plate solar water ...

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6th Parul international conference on Engineering and Technology, PICET 2024

作者： Hafez, Faizan M. Parmar, Kamlesh Parmar, Nirmal Department of Mechanical Engineering Parul Institute of Engineering and Technology Bharuch India Department of Mechanical Engineering Parul Institute of Engineering and Technology Vadodara India S.R.O Prague Zebra Technologies CZ Czech Republic

ISBN: (纸本)9798350369748

The world has been in greater need of energy over the past few years;thus, researchers have been working consistently on the development of solar energy-based applications. Solar based applications are one of the best options because it is endlessly abundant and perfect for both industries and domestic applications. The present review is majorly focused on studying the possibilities of using solar water heaters and optimizing a heating process with advanced machine learning for micro or/and small-scale industries in India. Small-scale industries such as hospitals, chemical plants, and waste management plants continuously require hot water. They primarily rely on electric heaters or/and gas heaters. These heaters run directly or indirectly on fossil fuels and may cause harm to the environment. To avoid the consumption of fossil fuels and to use solar energy as a primary energy source of heating, introducing solar water heating integrated with machine learning is worth exploring. Various thermal parameters such as mass flow rate, irradiation, tilt angle, wind speed, and designing parameters have their effects on the performance of solar water heating systems. The present article review conducted on the study of thermal parameters, nanofluid as a working heat transfer fluid, and machine learning use in solar water heating applications which can enhance the system performance. © 2024 IEEE.

关键词： Solar water heaters

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