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检索条件"任意字段=Proceedings of the 2023 4th International Conference on Machine Learning and Computer Application"

共 4166 条记录，以下是41-50 订阅

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Research on the Detection Methods for Changes in the Mangroves of Dongzhaigang, Hainan from 2019 to 2023 24

Research on the Detection Methods for Changes in the Mangrov...

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8th international conference on Electronic Information Technology and computer Engineering, EITCE 2024

作者： Zhang, Xianyao Lu, Huajun Qiu, Shuailong Liu, Lijin Wu, Zhongqiang School of Information Science and Technology Hainan Normal University Hainan Haikou China National Engineering Laboratory for Big Data System Computing Technology Shenzhen University Guangdong Shenzhen China

ISBN: (纸本)9798400710094

this study introduces the research methods for detecting changes in the mangroves of Dongzhaigang, Hainan from 2019 to 2023. Mangrove ecosystems play a crucial role in providing habitats and have ecological and economic value, but in recent years, they have faced degradation and management issues. In order to effectively monitor mangrove changes, researchers have utilized remote sensing techniques and machine learning methods for mangrove cover information extraction and classification. the paper describes the methods of estimating mangrove cover using remote sensing satellite imagery and spectral indices and explores the applications of clustering, decision trees, support vector machines, and deep learning in mangrove change detection. the research results indicate that the support vector machine algorithm performs well in classifying mangrove and non-mangrove areas. this study provides a basis for the management and decision-making of Dongzhaigang Mangrove Nature Reserve in Hainan Province and highlights the future research potential in the application of multi-source and multi-resolution data and deep learning techniques. © 2024 Copyright held by the owner/author(s).

关键词： Adversarial machine learning

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Leveraging AI for Dyslexia Detection: Exploring Multimodal Approaches with machine learning and Deep learning 4

Leveraging AI for Dyslexia Detection: Exploring Multimodal A...

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

作者： Priyasri, G.R. Devi, M. Uma Srm Institute of Science and Technology Department of Computing Technologies Kattankulathur Chengalpattu India

ISBN: (纸本)9798331523923

Developmental dyslexia is a learning disorder that typically begins in early childhood, making it difficult for affected individuals to read, write, and spell, even when they possess average or above-average intelligence. Children with dyslexia often experience negative emotions such as low selfesteem, frustration, and anger, highlighting the importance of early detection and intervention. Various methods have been proposed for detecting dyslexia, including reading and writing tests, eye tracking, facial image analysis, and advanced imaging techniques such as Magnetic Resonance Imaging (MRI) and Electroencephalography (EEG). However, one key challenge in dyslexia detection is the reliance on small, unbalanced datasets, which can lead to poor generalization in models. this review suggests that deep learning techniques, particularly those utilizing advanced data augmentation methods, could address this issue by enhancing the model's ability to learn from limited data, improving both accuracy and robustness in real-world applications. the review focuses on the use of machine learning (ML) and Deep learning (DL) for the automatic detection of dyslexia, aiming to improve diagnostic accuracy and accessibility. It explores various ML approaches, such as decision trees and support vector machines, as well as DL architectures, including Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs), which analyze text, speech, and eye-tracking patterns. the review provides a comparison of feature extraction methods, classification techniques, and performance metrics, with an emphasis on data enhancement and interpretability. Additionally, it addresses challenges such as dataset variability, ethical concerns, and the practical application of these methods in real-world settings. the goal of this review is to provide an overview of the most current methods for dyslexia detection and propose innovative ways to incorporate ML and DL into personalized learning plans an

关键词： Electroencephalography

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Smart Agricultural Greenhouse System: A Context-Aware application

Smart Agricultural Greenhouse System: A Context-Aware Applic...

引用

international conference on machine learning and Big Data Analytics, ICMLBDA 2023

作者： Swain, Sujata Niyogi, Rajdeep School of Computer Engineering Kalinga Institute of Industrial Technology Bhubaneswar India Department of Computer Science IIT Roorkee Roorkee India

ISBN: (纸本)9783031513374

Smart applications are getting more powerful and cheaper cost due to the advancement in sensor technology. In this chapter, we have considered a smart greenhouse application. the important parameters of the smart greenhouse are to control light, temperature, humidity, and water. Greenhouse can provide a favourable growth environment for plants. this smart greenhouse system is a context-aware application. When the context changes in the environment, the application automatically adapts it and does the changes seamlessly without user intervention. In this chapter, we propose a model for the smart greenhouse system. the proposed model can adapt to context changes such as temperature rises, and it automatically turns on the AC seamlessly. the proposed model is based on the machine learning approach. the model maintains the greenhouse temperature, humidity, and sunlight duration in the suitable ranges of the plant. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Context Greenhouse machine learning NLP Sensors Web service

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5th Asia-Pacific Web and Web-Age Information Management international Joint conference on Web and Big Data, APWeb-WAIM 2021, 4th international Workshop on Knowledge Graph Management and applications, KGMA 2021, 3rd international Workshop on Semi-structured Big Data Management and application, SemiBDMA 2021, and 2nd international Workshop on Deep learning in Large-scale Unstructured Data Analytics, DeepLUDA 2021

5th Asia-Pacific Web and Web-Age Information Management Inte...

引用

5th Asia-Pacific Web and Web-Age Information Management international Joint conference on Web and Big Data, APWeb-WAIM 2021, 4th international Workshop on Knowledge Graph Management and applications, KGMA 2021, 3rd international Workshop on Semi-structured Big Data Management and application, SemiBDMA 2021, and 2nd international Workshop on Deep learning in Large-scale Unstructured Data Analytics, DeepLUDA 2021

ISBN: (纸本)9789811681424

the proceedings contain 11 papers. the special focus in this conference is on Web and Big Data. the topics include: Survival Effect of Internet Macroscopic Topology Evolution;the Method for Image Noise Detection Based on the Amount of Knowledge Associated with Intuitionistic Fuzzy Sets;link Prediction of Heterogeneous Information Networks Based on Frequent Subgraph Evolution;memory Attentive Cognitive Diagnosis for Student Performance Prediction;A Study on the Privacy threat Analysis of PHI-Code;preface;should I Stay or Should I Go: Predicting Changes in Cluster Membership;logistics Policy Evaluation Model Based on Text Mining;MRRVOS: Modular Refinement Referring Video Object Segmentation.

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machine learning Techniques for Branch-and-Cut Methods: the Selection of Cutting Planes 4th

Machine Learning Techniques for Branch-and-Cut Methods: The...

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4th international conference on Numerical Computations: theory and Algorithms, NUMTA 2023

作者： Giallombardo, Giovanni Miglionico, Giovanna Sammarra, Marcello Arcavacata Italy Cosenza Italy

ISBN: (纸本)9783031812408

the selection of cuts to be added to the current LP relaxation is one of the most critical task in Branch-and-Cut methods, since it strongly affects the performances of the algorithm. Recently, machine learning techniques have become popular to define effective cut selection strategies. In this paper we explore the possibility of selecting cuts by ranking them via support vector regression. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Integer linear programming

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Federated learning: Concepts, application and Future Scope 4th

Federated Learning: Concepts, Application and Future Scope

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4th international conference on Smart IoT Systems: Innovations and Computing, SSIC 2023

作者： Jain, Pallav Patidar, Sanjay Delhi Technological University New Delhi India

ISBN: (纸本)9789819751990

Artificial is a constantly evolving and progressing technology. In today’s society, artificial intelligence models are frequently employed. With today’s data and the capabilities of artificial intelligence, we can attain human intellect and, in some situations, considerably more. But also, the rapid increase of data and how it is managed is a cause for concern. machine learning is an artificial intelligence sub-area that allows a machine to learn from prior data. Nowadays, machine learning is utilized in a broad range of applications. However, it is a tough task to apply machine learning on decentralized data. In the recent years, a new technique known as Federated learning has garnered considerable attention. It concentrates to train distributed and decentralized data while maintaining its privacy. In our paper we have explained what Federated learning is, the characteristics of Federated learning, what are the hardships we face in applying Federated learning, in which field Federated learning is currently used and what are the future scope of Federated learning. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Federated learning

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Enhanced Image-Text Retrieval Based on CLIP with YOLOv10 and Next-ViT 4

Enhanced Image-Text Retrieval Based on CLIP with YOLOv10 and...

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4th international conference on computer Vision, application, and Algorithm, CVAA 2024

作者： Qian, Xue Liu, Bo Beijing Information Science and Technology University Beijing China University of Westminster London United Kingdom

ISBN: (数字)9781510687622

ISBN: (纸本)9781510687615

In recent years, the CLIP model has achieved remarkable success in image-text retrieval tasks through contrastive learning. However, CLIP still exhibits certain limitations when handling complex backgrounds and small objects. To address these challenges, this paper proposes two key innovations: First, during inference, the YOLOv10 model is employed to detect and crop small objects and essential background information in the image, enhancing ability of CLIP to comprehend complex scenes. Second, the Next-ViT network is utilized as the backbone for image encoding. By leveraging its more efficient multi-scale feature extraction capabilities, Next-ViT improves the retrieval accuracy of small objects while also being more adaptable for deployment in industrial scenarios. Experimental results demonstrate that these two innovations significantly enhance performance of CLIP in image-text retrieval tasks and achieve a balance between accuracy and efficiency across various vision tasks. © 2025 SPIE.

关键词： Contrastive learning

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4th international conference on IoT and Big Data Technologies for Health Care, IotCare 2023

4th International Conference on IoT and Big Data Technologie...

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4th international conference on IoT and Big Data Technologies for Health Care, IotCare 2023

ISBN: (纸本)9783031900839

the proceedings contain 29 papers. the special focus in this conference is on IoT and Big Data Technologies for Health Care. the topics include: Research on Intelligent Mental Health Diagnosis and Treatment Big Data Anomaly Early Warning Algorithm;research on Nursing Service Quality Evaluation Model Based on Internet of things and Big Data Technology;research on Artificial Intelligence Medical Rapid Diagnosis Method Based on Sports Injury Data;research on Hierarchical Sharing Method of Athletes’ Physical Health Data Under the Background of Mobile Medicine;medical and Health Information Retrieval Method Based on Natural Language Processing;secure Storage Method of Students’ Mental Health Privacy Data Based on machine learning;Personalized Recommendation of TCM Pharmacy Distance Teaching Resources Based on Data Mining;research on the Method of Integrating Teaching Resources of Traditional Chinese Medicine Pharmacology Based on Deep learning Algorithm;research on Patients’ Choice Behavior in Online Health Community Based on Multi Source Data Analysis;multi Perspective Recommendation Method Based on Clustering Algorithm for Pharmaceutical Specialty Integration of Ideological and Political Teaching Materials;intelligent Evaluation Method of Students’ Mental Health Based on Internet of things Technology;monitoring and Warning Method of Students’ Mental Health Data Based on Internet of things;design of Low Delay Communication System for Emergency Medical Rescue Vehicle Based on Narrowband Internet of things;research on Intelligent Monitoring Method of Medical Financial Information Privacy Based on Internet of things;a Method of Classifying and Querying Student Mental Health Data Based on Internet of things Technology.

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Multi-label text classification method based on ReBERTa-TextCNN 4

Multi-label text classification method based on ReBERTa-Text...

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4th international conference on computer Vision, application, and Algorithm, CVAA 2024

作者： Zhang, Shengnan Xu, Huiyang Shenyang University of Technology School of Software Liaoning Shenyang China

ISBN: (数字)9781510687622

ISBN: (纸本)9781510687615

Multi Label Text Classification (MLTC) is an important research problem widely used in the field of natural language processing (NLP) text classification. Aiming at the problem of small sample data sets and unbalanced labels, this paper proposes a multi label text classification method based on prompt learning and RoBERTA Te People's Republic of China NN model. First, use the RoBERta model to obtain the label word vector in the text, and obtain the global features containing the text context information. the dynamic mask can improve the efficiency of the work. then use the Te People's Republic of China NN model to extract the local features of the text, and use the feature fusion method to fuse the global features and local features, so as to improve the classification accuracy of the model. Among them, prompt learning is used to process small sample data, and loss function is used to solve the problem of label imbalance and long tail distribution. the experiment on the actual dataset shows that the accuracy rate of multi label text classification reaches 96%, which reflects the advantage of this model in effectively improving the effect of multi label text classification. © 2025 SPIE.

关键词： Contrastive learning

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Research on dynamic network security detection technology based on SDN 4

Research on dynamic network security detection technology ba...

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4th international conference on Network Communication and Information Security, ICNCIS 2024

作者： Zhao, Kai Beijing Polytechnic Beijing100176 China

ISBN: (数字)9781510688261

ISBN: (纸本)9781510688254

Traditional network architecture can no longer meet the development needs of technologies such as cloud computing and big data. SDN network architecture has the characteristics of high openness and programmability, which can quickly respond to changes in business requirements. SDN decouples the control management function of the network from the data forwarding function, simplifies network configuration work based on logic centralized controllers and open programming interfaces, thereby achieving a flat management mode and flexible data forwarding function. the centralized control and programmability of SDN networks also pose significant security threats to SDN. Based on the CSE-CIC-IDS2018 dataset, this article tests the performance of various intelligent learning algorithms, analyzes data flows, distinguishes normal data from abnormal data, improves detection accuracy, and has practical significance for the security defense of SDN networks. © 2025 SPIE.

关键词： Network security computer security Network architectures Control systems machine learning Data transmission Defense and security Detection and tracking algorithms Information security Security technologies

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