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检索条件"任意字段=6th International Conference on Machine Learning and Data Mining in Pattern Recognition"

共 2833 条记录，以下是11-20 订阅

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Research on Optimization of Decision Support System Integrating Big data and machine learning 6

Research on Optimization of Decision Support System Integrat...

引用

6th IEEE international conference on Civil Aviation Safety and Information Technology, ICCASIT 2024

作者： Zhao, Xipeng Zhao, Fang Chen, Chunzi Computer Science National Meteorological Information Center Beijing100081 China

ISBN: (纸本)9798350389418

Owing to the latest innovations in big data technologies and progress of artificial intelligent modalities a number of fields have gone through a revolutionized decision making system. In this study research, the authors provide an optimal architecture of Decision Support System that appears to effectively integrate the big data analytics with the sophisticated machine learning algorithms to improve the decision making processes. the proposed system shares with big data platforms, a foundation of flexible and efficient technological solutions for handling large datasets. this is done through the use of machine learning algorithms for data prediction, data pattern recognition, and data decision making in real-time data bases. they highlighted that the optimization of the DSS architecture is another innovation of this research since it would lead to the enhancement of the accuracy, minimization of the latency and the user interface. To accomplish this research work to its best, numerous simulations of the system and real-case scenarios were carried out to evaluate the efficacy of the developed optimized system. these findings clearly illustrate increased levels of decision precision as well as decision-making speed. this research provides a sound solution for organizations that want to optimize the use of big data and incorporate machine learning methods into decision-making processes resulting in more savvy decisions. © 2024 IEEE.

关键词： Adversarial machine learning

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Credit Card Applications Based on data mining 6

Credit Card Applications Based on Data Mining

引用

6th international conference on machine learning, Big data and Business Intelligence, MLBDBI 2024

作者： Yuan, Yimeng College of Business The City University of Hong Kong Hong Kong Hong Kong

ISBN: (数字)9798331541798

ISBN: (纸本)9798331541798

this paper discusses the credit card application process based on data mining technology using principal component analysis (PCA) as an alternative to traditional methods to do variable selecting: weight of evidence(WOE) and information value(IV). Banks often transform historical data to credit scoring models and divide them into good or bad attribute to decide whether to accept credit from a customer. data usually include personality, capital, collateral, capacity. For credit card applicants, banks use credit scoring or predictive models to categories applicants and predict their future behaviour, which allows them to determine the probability of defaulting in a specific time frame in the future and thus optimizing model is particularly important. © 2024 IEEE.

关键词： Dimensionality reduction Analytical models Transforms Forestry Predictive models Credit cards data models data mining Business intelligence Principal component analysis

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2024 6th international conference on machine learning, Big data and Business Intelligence, MLBDBI 2024

2024 6th International Conference on Machine Learning, Big D...

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6th international conference on machine learning, Big data and Business Intelligence, MLBDBI 2024

ISBN: (纸本)9798331541798

the proceedings contain 57 papers. the topics discussed include: research on aspect-level emotion categorization based on hybrid attention mechanism;research on financial transaction data protection and intelligent risk assessment based on differential privacy;fine-tuned large language model for autonomous vehicles accident report;research on optimization strategy of production line in aviation manufacturing enterprises based on machine learning;research on factor interaction effects and nonlinear relationships in quantitative models;exploring emotion recognition in children with autism spectrum disorder using ChatGPT;and predicting user purchase behavior on ***: a sequential interaction and engagement depth model.

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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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Towards Full Population Testing in Auditing: How Many Process Deviations Should Be Labeled? 6

Towards Full Population Testing in Auditing: How Many Proces...

引用

6th international conference on Process mining (ICPM)

作者： Laghmouch, Manal Depaire, Benoit Jans, Mieke Hasselt Univ EDM Hasselt Belgium Maastricht Univ Maastricht Netherlands

ISBN: (纸本)9798350365030

Conformance checking allows auditors to detect process deviations automatically, resulting in numerous deviations, with only a few being relevant. Identifying notable items amidst this large data set is challenging. machine learning techniques offer potential solutions, but questions about the required number of labeled deviations and the impact of label quality remain. Our study investigates these factors' effects on Decision Trees and Random Forests. Results demonstrate these models' effectiveness in identifying notable items within imbalanced deviation populations. Achieving 90% precision and recall is feasible with about 400 to 600 labeled deviations, depending on the notable items' population fraction. A higher fraction of notables reduces the required labeled deviations. Varying label quality produced similar results. Additionally, classifications identifying at least 90% notable items are linked to less complex processes.

关键词： Auditing Conformance Checking Deviation Classification machine learning Notable Item Process Deviation Process mining

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mining CFD Algorithm on Medium dataset Using Queue 6

Mining CFD Algorithm on Medium Dataset Using Queue

引用

6th international conference on Cybernetics, Cognition and machine learning Applications, ICCCMLA 2024

作者： Baghel, Purva Pohekar, Poorva Gahukar, Suhani Pinjarkar, Latika Agrawal, Poorva Kaur, Gagandeep Nagpur campus Pune India

ISBN: (纸本)9798331505790

database and data mining is an important domain in the IT Sector as maintenance of big data leads to an increase in the accuracy and efficiency of projects working on the basis of the same datasets. In this research paper, the main aspect of data mining is discussed i.e., effective algorithms used for data mining and data analysis. We have discussed the algorithm for data mining CFD (Conditional Functional Dependency). Our goal is to find high-quality CFD relation sets. We have applied CFD on our college's medium data to filter the dirty items. In this experiment, we used a standard CFD and data structure like a queue to clean our data. We have selected the data of our college to clean up the data of the students who have left or didn't pass the degree. We evaluate our set of CFD by comparing them with the number of students enrolled and the number of degrees allotted to the students. We have also given examples on a small-scale basis about the above techniques and methods. © 2024 IEEE.

关键词： data accuracy

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Secured Challan Filling Automation using OCR Technology and machine learning 6

Secured Challan Filling Automation using OCR Technology and ...

引用

6th international conference on Mobile Computing and Sustainable Informatics, ICMCSI 2025

作者： Sivakumar, Adhithya Mohan, Karthick Elango, Gunasekar Jayakumar, Nithya Department of Information Technology K.S.Rangasamy College of Technology Tiruchengode India

ISBN: (纸本)9798331522667

the Automated Challan Filling System integrates several advanced technologies, such as Optical Character recognition (OCR), machine learning (ML), and voice assistance to modernize the bank challan process. Such technologies reduce manual entries and errors in the physical forms by automatically extracting key data from *** helps validate the accuracy of data in addition to detecting false cases for enhanced security. the option of multiple authentication methods such as PIN, OTP, and biometric avenues ensures secure, personalized transactions. With a voice assistant that guides users step-by-step, it makes the system user-friendly, especially to literate and non-literate and low-tech users. Multilingual and with a user-friendly interface, the system enhances accessibility, efficiency, and transaction speed in addressing the disadvantaged users’ challenges in accessing traditional banking processes. © 2025 IEEE.

关键词： Optical character recognition

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Research on Optical Mineral Image recognition Based on Federated learning 6

Research on Optical Mineral Image Recognition Based on Feder...

引用

6th international conference on Next Generation data-Driven Networks, NGDN 2024

作者： Guo, Zhenzhou Liu, Ao Dong, Rongchang Shenyang Aerospace University School of Artificial Intelligence Shenyang China

ISBN: (纸本)9798350388374

the ability to recognize optical images of minerals has advanced significantly in today's culture, but there are still two obstacles to overcome: (1) Due to industry secrecy, mineral data usually exists in the form of "data silos"in the local mines. It is difficult to train a good recognition model from these data because of the fixed types of minerals in a single mine. (2) In the case that the local data set of a single mine is not sound, optical mineral image recognition is needed to assist the actual production application. For the aforementioned reasons, this paper proposes a horizontal federated learning scheme based on FedMoon and ConvNeXt, and ensures the security of data transmission through the introduction of noise by differential privacy, so as to ensure the security and at the same time integrate the independent samples from each mine to improve the recognition accuracy of optical mineral images, and then send them to the mines for use. the studies show that the proposed scheme in this paper is more effective than the independently trained image recognition model of a single mine in the federated learning scenario, which proves that the federated learning framework has a wide range of application prospects in the mining industry. © 2024 IEEE.

关键词： Differential privacy

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Applications of machine learning in Corrosion Detection 6

Applications of Machine Learning in Corrosion Detection

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6th international conference on pattern Analysis and Intelligent Systems, PAIS 2024

作者： Daoudi, Nessreddin Haouam, Mohamed Yassine Laimeche, Lakhdar Bendib, Issam Amroune, Mohamed Tebessa Algeria

ISBN: (纸本)9798350350265

the increasing challenges associated with corrosion in various industries have prompted the exploration of advanced techniques for detection and prediction. this review paper comprehensively examines the application of machine learning in corrosion detection. Leveraging a diverse set of datasets, including X-ray computed tomography (XCT), NEA, CAMCD, and a specialized dataset for Cross-country Pipeline Inspection data Analysis and Testing of Probabilistic Degradation Models, we explore the efficacy of machine learning algorithms. the review highlights segmentation and classification techniques, emphasizing their role in accurate corrosion identification. Insights derived from this review contribute to the ongoing efforts to enhance corrosion monitoring and preventive strategies. © 2024 IEEE.

关键词： Computerized tomography

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machine learning techniques during the COVID-19 Pandemic: A Bibliometric Analysis 6

Machine learning techniques during the COVID-19 Pandemic: A ...

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6th international conference on pattern recognition and Image Analysis (IPRIA)

作者： Alavi, Meysam Valiollahi, Arefeh Kargari, Mehrdad Tarbiat Modares Univ Dept Informat Technol Tehran Iran

ISBN: (纸本)9798350314557

the Coronavirus pandemic (COVID-19) has encouraged researchers to produce significant scientific research in this field in reputable international citation databases. It is important to constantly identify and assess scientific outputs in order to learn more about the situation. One of the methods used for evaluating scientific research activities is scientometrics, which has many applications in describing, explaining and predicting the scientific status of researchers and research centers in various national and international fields. It also provides efficient methods for monitoring and ranking organizations, researchers, journals and countries. On the other hand, in recent years, the use of various scientometric techniques, including co-word analysis, co-authorship network and scientific network, has been of great help in discovering the direction of researchers' production in scientific domain and its hidden and overt dimensions. One of the most popular areas since the COVID-19 epidemic started, has been research the use of artificial intelligence and especially machine learning techniques in the prediction, diagnosis and treatment of this disease. In this regard, 2659 documents from the PubMed citation database since the start of the COVID-19 epidemic have been reviewed. the findings of this research show that America, China, India and England are the countries that have cooperated the most with other countries. In addition, the results of this research showed that deep learning and CNN had been significantly used in the researchers' studies.

关键词： COVID-19 machine learning techniques Bibliometric analysis Co-word analysis

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