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检索条件"机构=Machine Learning and Data Analytics Research"
71 条 记 录,以下是21-30 订阅
排序:
Stroke Home Rehabilitation Approach Using Mobile Application Based on PostNet machine learning Model  23
Stroke Home Rehabilitation Approach Using Mobile Application...
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7th International Conference on Medical and Health Informatics, ICMHI 2023
作者: Das, Utpal Chandra Le, Ngoc Thien Benjapolakul, Watit Vitoonpong, Timporn Pluempitiwiriyawej, Charnchai Center of Excellence in Artificial Intelligence Machine Learning and Smart Grid Technology Department of Electrical Engineering Chulalongkorn University Bangkok10330 Thailand Department of Rehabilitation Medicine Faculty of Medicine Chulalongkorn University Bangkok10330 Thailand Multimedia Data Analytics and Processing Research Unit Department of Electrical Engineering Faculty of Engineering Chulalongkorn University Bangkok10330 Thailand
Stroke is a significant cause of mortality and disability globally, with its occurrence in the human brain and motor function being linked to various parts of the human body. Stroke victims often experience disabiliti... 详细信息
来源: 评论
Bias Bubbles: Using Semi-Supervised learning to Measure How Many Biased News Articles Are Around Us  29
Bias Bubbles: Using Semi-Supervised Learning to Measure How ...
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29th Irish Conference on Artificial Intelligence and Cognitive Science, AICS 2021
作者: Ruan, Qin Namee, Brian Mac Dong, Ruihai School of Computer Science University College Dublin Dublin Ireland Insight Centre for Data Analytics Science Foundation Ireland Centre for Research Training in Machine Learning Ireland
The proliferation of web 2.0 technology allows us to easily create and share online content, but also leads to the rapid spread of misinformation and biased media, which has considerable negative effects on society. D... 详细信息
来源: 评论
data-driven Energy Consumption Modelling for Electric Micromobility using an Open dataset
Data-driven Energy Consumption Modelling for Electric Microm...
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IEEE Transportation Electrification Conference and Expo (ITEC)
作者: Yue Ding Sen Yan Maqsood Hussain Shah Hongyuan Fang Ji Li Mingming Liu SFI Centre for Research Training in Machine Learning (ML-Labs) Dublin City University SFI Insight Centre for Data Analytics and the School of Electronic Engineering Dublin City University Dublin Ireland Department of Mechanical Engineering University of Birmingham
The escalating challenges of traffic congestion and environmental degradation underscore the critical importance of embracing E-Mobility solutions in urban spaces. In particular, micro E-Mobility tools such as E-scoot... 详细信息
来源: 评论
Rethinking Knee Osteoarthritis Severity Grading: A Few Shot Self-Supervised Contrastive learning Approach
arXiv
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arXiv 2024年
作者: Belton, Niamh Hagos, Misgina Tsighe Lawlor, Aonghus Curran, Kathleen M. Science Foundation Ireland Centre for Research Training in Machine Learning School of Medicine University College Dubline Ireland School of Computer Science University College Dublin Ireland Insight Centre for Data Analytics University College Dublin Dublin Ireland
Knee Osteoarthritis (OA) is a debilitating disease affecting over 250 million people worldwide. Currently, radiologists grade the severity of OA on an ordinal scale from zero to four using the Kellgren-Lawrence (KL) s... 详细信息
来源: 评论
System Architecture for Reading and Interpreting Physical Printouts of Medical Forms  22
System Architecture for Reading and Interpreting Physical Pr...
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22nd IEEE International Conference of Young Professionals in Electron Devices and Materials, EDM 2021
作者: Snegireva, Ekaterina Khazankin, Grigory R. Mikheenko, Igor Stream Data Analytics and Machine Learning Laboratory Novosibirsk State University Novosibirsk Russia Novosibirsk State University Novosibirsk Russia Meshalkin National Medical Research Center Novosibirsk Russia
This article describes the developed architecture of the system module for processing and interpreting analog medical data. Patients often undergo examinations in various medical institutions, and since their results ... 详细信息
来源: 评论
Miscellaneous EEG Preprocessing and machine learning for Pilots' Mental States Classification: Implications  22
Miscellaneous EEG Preprocessing and Machine Learning for Pil...
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Proceedings of the 6th International Conference on Advances in Artificial Intelligence
作者: Ibrahim Mohammad Alreshidi Irene Moulitsas Karl W. Jenkins Centre for Computational Engineering Sciences Cranfield University UK and Machine Learning and Data Analytics Laboratory Digital Aviation Research and Technology Centre (DARTeC) UK Centre for Computational Engineering Sciences Cranfield University UK
Higher cognitive process efforts may result in mental exhaustion, poor performance, and long-term health issues. An EEG-based methods for detecting a pilot's mental state have recently been created utilizing machi... 详细信息
来源: 评论
FewSOME: One-Class Few Shot Anomaly Detection with Siamese Networks
FewSOME: One-Class Few Shot Anomaly Detection with Siamese N...
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IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
作者: Niamh Belton Misgina Tsighe Hagos Aonghus Lawlor Kathleen M. Curran Science Foundation Ireland Centre for Research Training in Machine Learning School of Medicine University College Dublin School of Computer Science University College Dublin Insight Centre for Data Analytics University College Dublin Dublin Ireland
Recent Anomaly Detection techniques have progressed the field considerably but at the cost of increasingly complex training pipelines. Such techniques require large amounts of training data, resulting in computational...
来源: 评论
NC-ALG: Graph-Based Active learning Under Noisy Crowd
NC-ALG: Graph-Based Active Learning Under Noisy Crowd
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International Conference on data Engineering
作者: Wentao Zhang Yexin Wang Zhenbang You Yang Li Gang Cao Zhi Yang Bin Cui Center for Machine Learning Research Peking University Institute of Advanced Algorithms Research Shanghai National Engineering Labratory for Big Data Analytics and Applications Key Lab of High Confidence Software Technologies Peking University Department of Data Platform TEG Tencent Inc. Beijing Academy of Artificial Intelligence Institute of Computational Social Science Peking University Qingdao
Graph Neural Networks (GNNs) have achieved great success in various data mining tasks but they heavily rely on a large number of annotated nodes, requiring considerable human efforts. Despite the effectiveness of exis... 详细信息
来源: 评论
BIM: Improving Graph Neural Networks with Balanced Influence Maximization
BIM: Improving Graph Neural Networks with Balanced Influence...
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International Conference on data Engineering
作者: Wentao Zhang Xinyi Gao Ling Yang Meng Cao Ping Huang Jiulong Shan Hongzhi Yin Bin Cui Center for Machine Learning Research Peking University Institute of Advanced Algorithms Research Shanghai National Engineering Labratory for Big Data Analytics and Applications The University of Queensland Australia Key Lab of High Confidence Software Technologies Peking University Apple Inc. Institute of Computational Social Science Peking University Qingdao
The imbalanced data classification problem has aroused lots of concerns from both academia and industry since data imbalance is a widespread phenomenon in many real-world scenarios. Although this problem has been well... 详细信息
来源: 评论
Design and Implementation of a data Governance Framework and Platform: A Case Study of a National research Organization of Thailand
Design and Implementation of a Data Governance Framework and...
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International Joint Conference on Computer Science and Software Engineering (JCSSE)
作者: Sapa Chanyachatchawan Krich Nasingkun Patipat Tumsangthong Porntiwa Chata Marut Buranarach Monsak Socharoentum Leveraging Technology Solutions Section National Electronics and Computer Technology Center Bangkok Thailand Strategic Analytics Networks with Machine Learning and AI Research National Electronics and Computer Technology Center Bangkok Thailand Data Science and Analytics Research Group National Electronics and Computer Technology Center Bangkok Thailand Digital Government Development Agency Bangkok Thailand
In the current era of extensive data usage across industries, data collection, preservation, utilization, and organization has become more challenging and nuanced because it is necessary to consider critical concerns ...
来源: 评论