检索结果-内蒙古大学图书馆

The Journal of machine learning Research 2022年第1期23卷 4632-4660页

作者： Christoffer Löffler Christopher Mutschler Machine Learning and Data Analytics Lab Friedrich-Alexander University Erlangen-Nürnberg (FAU) Erlangen Germany Fraunhofer IIS Fraunhofer Institute for Integrated Circuits IIS Nuremberg Germany

Active learning prioritizes the lab.ling of the most informative data samples. However, the performance of active learning heuristics depends on both the structure of the underlying model architecture and the data. We propose IALE, an imitation learning scheme that imitates the selection of the best-performing expert heuristic at each stage of the learning cycle in a batch-mode pool-based setting. We use DAGGER to train a transferable policy on a dataset and later apply it to different datasets and deep classifier architectures. The policy reects on the best choices from multiple expert heuristics given the current state of the active learning process, and learns to select samples in a complementary way that unifies the expert strategies. Our experiments on well-known image datasets show that we outperform state of the art imitation learners and heuristics.

关键词： active learning deep neural networks imitation learning dataset aggregation transferable policy

来源：评论

学校读者我要写书评

暂无评论

Automatic clinical gait test detection from inertial sensor data

Automatic clinical gait test detection from inertial sensor ...

引用

Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： Stefan Fischer Martin Ullrich Arne Küderle Heiko Gaßner Jochen Klucken Bjoern M. Eskofier Felix Kluge Machine Learning and Data Analytics Lab Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) Germany University Hospital Erlangen Germany

ISBN: (数字)9781728119908

ISBN: (纸本)9781728119915

The analysis of gait data is one approach to support clinicians with the diagnosis and therapy of diseases, for example Parkinson's disease (PD). Traditionally, gait data of standardized tests in the clinic is analyzed, ensuring a predefined setting. In recent years, long-term home-based gait analysis has been used to acquire a more representative picture of the patient's disease status. data is recorded in a less artificial setting and therefore allows a more realistic perception of the disease progression. However, fully unsupervised gait data without additional context information impedes interpretation. As an intermediate solution, performance of gait tests at home was introduced. Integration of instrumented gait test requires annotations of those tests for their identification and further processing. To overcome these limitations, we developed an algorithm for automatic detection of standardized gait tests from continuous sensor data with the goal of making manual annotations obsolete. The method is based on dynamic time warping, which compares an input signal with a predefined template and quantifies similarity between both. Different templates were compared and an optimized template was created. The classification scored a F1-measure of 86.7% for evaluation on a data set acquired in a clinical setting. We believe that this approach can be transferred to home-monitoring systems and will facilitate a more efficient and automated gait analysis.

关键词： Turning Diseases Instruments Legged locomotion Gyroscopes Hospitals Reliability

来源：评论

学校读者我要写书评

暂无评论

A.I. and data-Driven Mobility at Volkswagen Financial Services AG

arXiv

引用

arXiv 2022年

作者： Jawed, Shayan Arif, Mofassir Ul Islam Rashed, Ahmed Madhusudhanan, Kiran Elsayed, Shereen Jameel, Mohsan Schmidt-Thieme, Lars Volk, Alexei Hintsches, Andre Kornfeld, Marlies Lange, Katrin Information Systems and Machine Learning Lab University of Hildesheim Germany Data Analytics & A.I Unit Volkswagen Financial Services AG Germany

machine learning is being widely adapted in industrial applications owing to the capabilities of commercially availab.e hardware and rapidly advancing research. Volkswagen Financial Services (VWFS), as a market leader in vehicle leasing services, aims to leverage existing proprietary data and the latest research to enhance existing and derive new business processes. The collab.ration between Information Systems and machine learning lab.(ISMLL) and VWFS serves to realize this goal. In this paper, we propose methods in the fields of recommender systems, object detection, and forecasting that enable data-driven decisions for the vehicle life-cycle at VWFS. © 2022, CC BY-NC-ND.

关键词： machine learning

来源：评论

学校读者我要写书评

暂无评论

Gaitmap - An Open Ecosystem for IMU-based Human Gait Analysis and Algorithm Benchmarking

TechRxiv

引用

TechRxiv 2023年

作者： Küderle, Arne Ullrich, Martin Roth, Nils Ollenschläger, Malte Ibrahim, Alzhraa Moradi, Hamid Richer, Robert Seifer, Ann-Kristin Zürl, Matthias Sîmpetru, Raul Herzer, Liv Prossel, Dominik Kluge, Felix Eskofier, Bjoern Friedrich-Alexander-Universität Erlangen-Nürnberg Machine Learning and Data Analytics Lab Department of Artificial Intelligence in Biomedical Engineering Germany

来源：评论

学校读者我要写书评

暂无评论

Digitizing handwriting with a sensor pen: A writer-independent recognizer

arXiv

引用

arXiv 2021年

作者： Wehbi, Mohamad Hamann, Tim Barth, Jens Eskofier, Bjoern Machine Learning and Data Analytics Lab Friedrich-Alexander-Universität Erlangen-Nürnberg Erlangen Germany STABILO International GmbH Heroldsberg Germany

Online handwriting recognition has been studied for a long time with only few practicable results when writing on normal paper. Previous approaches using sensor-based devices encountered problems that limited the usage of the developed systems in real-world applications. This paper presents a writer-independent system that recognizes characters written on plain paper with the use of a sensor-equipped pen. This system is applicable in real-world applications and requires no user-specific training for recognition. The pen provides linear acceleration, angular velocity, magnetic field, and force applied by the user, and acts as a digitizer that transforms the analogue signals of the sensors into timeseries data while writing on regular paper. The dataset we collected with this pen consists of Latin lower-case and upper-case alphabets. We present the results of a convolutional neural network model for letter classification and show that this approach is practical and achieves promising results for writer-independent character recognition. This work aims at providing a realtime handwriting recognition system to be used for writing on normal paper. © 2021, CC BY.

关键词： Character recognition

来源：评论

学校读者我要写书评

暂无评论

A Generic and Robust System for Automated Detection of Different Classes of Arrhythmia

引用

Procedia Computer Science 2020年 167卷 1801-1810页

作者： Vandana Singh U. Srinivasulu Reddy G. Manju Bhargavia M.Tech (Data Analytics) National Institute of Technology Tiruchirappalli 620015 India Assistant Professor Machine Learning and Data Analytics Lab Department of Computer Applications National Institute of Technology Tiruchirappalli 620015 India Post-Doc Department of Physics National Institute of Technology Tiruchirappalli 620015 India

Cardiovascular Arrhythmias (irregular beat) are related to the sudden death, can be characterized into two kinds, life-threatening (dangerous) and non-life-threatening. In clinical research and diagnosis analysis electrocardiography (ECG) plays an important role. The Advancement of Medical Instrumentation (AAMI) suggests, all the heartbeat of MIT-BIH dataset into four classes, namely, normal or bundle branch block (N), supraventricular ectopic (S), ventricular ectopic (V) and fusion of ventricular and normal (F). The objective of this paper is the classification of arrhythmias on the ECG as per AAMI standards. First beat detection and then on a given window size beat segmentation is performed. Then, features computed from ECG signals are RR (separation between two successive heartbeat pulses), local binary pattern(LBP), morphological changes, wavelet, high order statistics, and several amplitude values; Pre-RR, Post-RR, Local RR and Global RR. The main reason is to computing many morphological features to comparison analysis with the model when trained and tested on single features vs combining all features together. Model gives highest performance which is 90.8% accuracy using LBP as single feature compared with other features. Combined all important features together and optimal features (total 104 ) are given as an input to Single SVM classifier as well as ensembles of SVM which maps the component feature vectors to the particular class name. Principal Component Analysis (PCA) technique is also applied to the model which reduces the total number of features from 104 to 30 features. The Single SVM system can accurately classify four beat types and has an overall classification rate of 94.05% without PCA and using PCA 92.84% while the Ensemble SVM classifies and with an accuracy of 92.96%

关键词： Electrocardiogram (ECG) signal MIT-BIH dataset Wavelet Transform Support Vector machines OVO

来源：评论

学校读者我要写书评

暂无评论

Digitizing Handwriting with a Sensor Pen: A Writer-Independent Recognizer

Digitizing Handwriting with a Sensor Pen: A Writer-Independe...

引用

International Workshop on Frontiers in Handwriting Recognition

作者： Mohamad Wehbi Tim Hamann Jens Barth Bjoern Eskofier Machine Learning and Data Analytics Lab Friedrich-Alexander-Universität Erlangen-Nürnberg Erlangen Germany STABILO International GmbH Heroldsberg Germany

ISBN: (数字)9781728199665

ISBN: (纸本)9781728199672

Online handwriting recognition has been studied for a long time with only few practicable results when writing on normal paper. Previous approaches using sensor-based devices encountered problems that limited the usage of the developed systems in real-world applications. This paper presents a writer-independent system that recognizes characters written on plain paper with the use of a sensor-equipped pen. This system is applicable in real-world applications and requires no user-specific training for recognition. The pen provides linear acceleration, angular velocity, magnetic field, and force applied by the user, and acts as a digitizer that transforms the analogue signals of the sensors into timeseries data while writing on regular paper. The dataset we collected with this pen consists of Latin lower-case and upper-case alphabets. We present the results of a convolutional neural network model for letter classification and show that this approach is practical and achieves promising results for writer-independent character recognition. This work aims at providing a real-time handwriting recognition system to be used for writing on normal paper.

关键词： Writing Character recognition Handwriting recognition Optical character recognition software data models Training Real-time systems

来源：评论

学校读者我要写书评

暂无评论

Real-time Mental State Recognition using a Wearable EEG

Real-time Mental State Recognition using a Wearable EEG

引用

Annual International Conference of the IEEE Engineering in Medicine and Biology Society

作者： Robert Richer Nan Zhao Judith Amores Bjoern M. Eskofier Joseph A. Paradiso Machine Learning and Data Analytics Lab Friedrich-Alexander-Universitt Erlangen-Nrnberg (FAU) Erlangen Germany Massachusetts Institute of Technology Media Lab Cambridge MA US

The increasing quality and availab.lity of low-cost EEG systems offer new possibilities for non-medical purposes. Existing openly availab.e algorithms to assess the user's mental state in real-time have been mainly performed with medical-grade equipment. In this paper, an approach to assess the user's Focus or Relax states in real-time using a consumer-grade, wearable EEG headband is evaluated. One naive measure and four entropy-based measures, computed using relative frequency band powers in the EEG signal, were introduced. Classifiers for relax and focus state detection, based on the estimation of probability distributions, were developed and evaluated in a user study. Results showed that the Tsallis entropy-based measure performed best for the Focus score, whereas the Renyi measure performed best for the Relax score. Sensitivities of 82.0% and 80.4% with specificities of 82.8% and 80.8% were achieved for the Focus and Relax scores, respectively. The results demonstrated the possibilities of using a wearable EEG system for real-time mental state recognition.

关键词： Electroencephalography Entropy Real-time systems Task analysis Histograms Frequency measurement Sensitivity

来源：评论

学校读者我要写书评

暂无评论

Supervised learning for Yaw Orientation Estimation

Supervised Learning for Yaw Orientation Estimation

引用

International Conference on Indoor Positioning and Indoor Navigation (IPIN)

作者： Tobias Feigl Christopher Mutschler Michael Philippsen Machine Learning and Information Fusion Group Fraunhofer Institute for Integrated Circuits IIS Nuremberg Germany Machine Learning and Data Analytics Lab Friedrich-Alexander University Erlangen-Nürnberg Erlangen Germany Programming Systems Group

With free movement and multi-user capabilities, there is demand to open up Virtual Reality (VR) for large spaces. However, the cost of accurate camera-based tracking grows with the size of the space and the number of users. No-pose (NP) tracking is cheaper, but so far it cannot accurately and stably estimate the yaw orientation of the user's head in the long-run. Our novel yaw orientation estimation combines a single inertial sensor located at the human's head with inaccurate positional tracking. We exploit that humans tend to walk in their viewing direction and that they also tolerate some orientation drift. We classify head and body motion and estimate heading drift to enable low-cost long-time stable head orientation in NP tracking on 100 m×100 m. Our evaluation shows that we estimate heading reasonably well.

关键词： Magnetic heads Feature extraction Acceleration Tracking Head Accelerometers Estimation

来源：评论

学校读者我要写书评

暂无评论

Indoor Positioning Using OFDM-Based Visible Light Communication System

Indoor Positioning Using OFDM-Based Visible Light Communicat...

引用

International Conference on Indoor Positioning and Indoor Navigation (IPIN)

作者： Birendra Ghimire Jochen Seitz Christopher Mutschler Precise Positioning and Analytics Department Fraunhofer Institute for Integrated Circuits IIS Nürnberg Germany Machine Learning and Data Analytics Lab Friedrich-Alexander University Erlangen-Nürnberg (FAU) Erlangen Germany

Precise indoor positioning is essential to support emerging applications of location aware mobile computing. Current positioning techniques that use signals transmitted in the Gigahertz region of radio-frequency spectrum do not provide highly accurate position estimates due to multipath propagation of signals. This paper proposes a novel positioning system which uses the entities of visible light communication (VLC) system as anchors and tags. Our technique scales with the number of tags and the VLC network provides both positioning and communication capabilities. The anchor points transmit the OFDM-based VLC signals synchronously, and we estimate the time differences of arrival between anchor points and tags using positioning reference signals embedded into the air-interface of the VLC system. Simulation results show that positioning accuracy of 10 cm or better is possible for over 95% of users if the sampling clock offset is better that 10 ppm, clock jitter is below 1 ps, and a bit resolution of at least 16 bits is availab.e.

关键词： Light emitting diodes OFDM Optical receivers Adaptive optics Optical filters Measurement uncertainty

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：