NSTL国家科技图书文献中心

1. Refining Human-Data Interaction: Advanced Techniques for EEGEyeNet Dataset Precision NSTL国家科技图书文献中心

Jade Wu | Jingwen Dou ... - 《HCI International 2024 - Late Breaking Papers,Part I》 - International Conference on Human-Computer Interaction - 2025, - 407～419 - 共13页

摘要： outlier removal. By identifying and eliminating outliers | The EEGEyeNet dataset merges EEG data with eye | -tracking technology to advance cognitive research at the | intersection of brain dynamics and eye movement. By | developing machine learning models to predict eye movements

关键词： EEG | Gaze prediction | Machine learning | Vision transformer | EEGEyeNet | Data preprocessing

2. Adaptive spindle fusion clustering algorithm for millimeter wave radar traffic targets NSTL国家科技图书文献中心

Wei Xu | Qinlin Li ... - 《Fourth International Conference on Intelligent Traffic Systems and Smart City (ITSSC 2024)》 - International Conference on Intelligent Traffic Systems and Smart City - 2025, - 134221D.1～134221D.9 - 共9页

摘要： outlier removal on the radar data, and secondary | How to accurately acquire and track the | positions of multiple vehicles in a traffic system is a | challenging problem. Especially in the clustering detection | problem, the uncertainty of vehicle states (including

关键词： FMCW | Radar | Multi-target point cloud clustering | DBSCAN | Velocity-clustering | Multi-dimensional clustering fusion

3. Performance Evaluation of Data Analysis Techniques in Dry Bean Seed Classification Using kNN and MLP NSTL国家科技图书文献中心

Victor Hugo Schneide... | Alessandro Bof de Ol...... - 《Advances in Artificial Intelligence》 - Ibero-American Conference on Artificial Intelligence - 2025, - 323～334 - 共12页

摘要： techniques, such as missing value imputation, outlier | removal, and data normalization, were applied. The k | Seed classification, particularly for dry bean | seeds, is crucial for ensuring high agricultural | productivity and efficiency. This paper investigates the

关键词： Machine learning | Data analysis | Beans seed classification

4. A method for extracting road markings based on vehicle-mounted LiDAR point clouds NSTL国家科技图书文献中心

Yong He | Tao Zou ... - 《Fourth International Conference on Intelligent Traffic Systems and Smart City (ITSSC 2024)》 - International Conference on Intelligent Traffic Systems and Smart City - 2025, - 134221H.1～134221H.11 - 共11页

摘要： thresholding method and Statistical Outlier* Removal (SOR* | This paper proposes an automatic road marking | extraction method based on vehicle-mounted laser scanning | data. First, the grid elevation difference threshold | method is used to segment the point cloud data into

关键词： Vehicle-mounted laser point cloud | Gridding | Intensity feature image | Road marking extraction

5. Predicting Cutter Wear in Shield Tunneling Construction Using Machine Learning:A Case Study from Chunfeng Road Tunnel Project in China NSTL国家科技图书文献中心

Xiaobin Ding | Linxuan Yuan ... - 《Information technology in geo-engineering》 - International Conference on Information Technology in Geo-engineering - 2025, - 3～12 - 共10页

摘要： across each tunnel ring,followed by outlier removal | Shield tunneling construction is a predominant | method in metro infrastructure development,where the | wear of tunnel boring machine(TBM)cutters is a | critical issue that slows down its construction.The

关键词： Machine Learning | Cutter Wear Prediction | 1 D-Convolutional Neural Network

6. Interpretable Unsupervised Homography Estimation NSTL国家科技图书文献中心

Zhen Zhou | Qing Zhu ... - 《Pattern Recognition and Computer Vision,Part II》 - Chinese Conference on Pattern Recognition and Computer Vision - 2025, - 391～405 - 共15页

摘要： removal and mask generation. Specifically, we select | alignment as outlier* detection. The pixel-level support* | Homography estimation is a common image | alignment method. Existing methods of learning focused | principal plane masks through deep neural networks lack

关键词： Homography estimation | Pixel-level SVDD | Gaussian density estimation | Correlation learning module

7. A calibration method based on outlier-removal for high-accuracy uniaxial MEMS-based reconstruction NSTL国家科技图书文献中心

Yaohui Zhu | Min Han ... - 《Semiconductor Lasers and Applications XIV》 - Semiconductor Lasers and Applications (conference) - 2024, - 共8页

摘要： global calibration method based on an outlier removal | outlier removal mechanism enhances the accuracy of | High-accuracy calibration of uniaxial MEMS | -based systems is essential for achieving precise 3D | reconstructions because the calibration results will directly

关键词： Calibration | Outlier removal | Uniaxial MEMS | Fringe projection profilometry

8. HEART RATE VARIABILITY ESTIMATION WITH DYNAMIC FINE FILTERING AND GLOBAL-LOCAL CONTEXT OUTLIER REMOVAL NSTL国家科技图书文献中心

Ramesh Kumar Sah | Md. Mahbubur Rahman ... - 《ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2024), Vol.3: Seoul, South Korea.14-19 April 2024》 - IEEE International Conference on Acoustics, Speech and Signal Processing - 2024, - 2091～2095 - 共5页

摘要： improved the inter-beat interval (IBI) outlier* detection* | and removal* algorithm using the global-local context* | Consumer bearable technologies such as | earbttds are increasingly embedding physiological sensors | , including photo-plethysmography (PPG) and inertial

关键词： PPG | HRV | outlier removal | signal quality

9. LOCO-PCR: A Novel Outlier Removal Method with Local Correction for Feature-based Point Cloud Registration NSTL国家科技图书文献中心

Yunhui Zhong | Jianliang Ma ... - 《2024 36th Chinese Control and Decision Conference,[v.1]》 - Chinese Control and Decision Conference - 2024, - 4948～4955 - 共8页

摘要： registration (PCR). In this paper, we present a novel outlier | removal method, which locally corrects (LOCO) the | Finding reliable correspondences between two | point clouds is crucial for feature-based point cloud | initial correspondences to generate more correct

关键词： Point cloud compression | Training | Accuracy | Three-dimensional displays | Noise | Interference | Stability analysis

10. Pragmatic EDA Flow Runtime Prediction with Machine Learning and Automatic Outlier Removal NSTL国家科技图书文献中心

I-Lun Tseng - 《2024 IEEE Asia Pacific Conference on Circuits and Systems》 - IEEE Asia Pacific Conference on Circuits and Systems | IEEE Asia Pacific Conference on Postgraduate Research in Microelectronics and Electronics - 2024, - 203～207 - 共5页

摘要： allows automatic removal* of outliers and does not* | As semiconductor process technology advances | , the runtimes of electronic design automation (EDA | ) jobs have become increasingly challenging. At the 3nm | process node, for example, a digital circuit design or

摘要： outlier removal. By identifying and eliminating outliers | The EEGEyeNet dataset merges EEG data with eye | -tracking technology to advance cognitive research at the | intersection of brain dynamics and eye movement. By | developing machine learning models to predict eye movements

关键词： EEG | Gaze prediction | Machine learning | Vision transformer | EEGEyeNet | Data preprocessing

摘要： outlier removal on the radar data, and secondary | How to accurately acquire and track the | positions of multiple vehicles in a traffic system is a | challenging problem. Especially in the clustering detection | problem, the uncertainty of vehicle states (including

关键词： FMCW | Radar | Multi-target point cloud clustering | DBSCAN | Velocity-clustering | Multi-dimensional clustering fusion

摘要： techniques, such as missing value imputation, outlier | removal, and data normalization, were applied. The k | Seed classification, particularly for dry bean | seeds, is crucial for ensuring high agricultural | productivity and efficiency. This paper investigates the

关键词： Machine learning | Data analysis | Beans seed classification

摘要： thresholding method and Statistical Outlier* Removal (SOR* | This paper proposes an automatic road marking | extraction method based on vehicle-mounted laser scanning | data. First, the grid elevation difference threshold | method is used to segment the point cloud data into

关键词： Vehicle-mounted laser point cloud | Gridding | Intensity feature image | Road marking extraction

摘要： across each tunnel ring,followed by outlier removal | Shield tunneling construction is a predominant | method in metro infrastructure development,where the | wear of tunnel boring machine(TBM)cutters is a | critical issue that slows down its construction.The

关键词： Machine Learning | Cutter Wear Prediction | 1 D-Convolutional Neural Network

摘要： removal and mask generation. Specifically, we select | alignment as outlier* detection. The pixel-level support* | Homography estimation is a common image | alignment method. Existing methods of learning focused | principal plane masks through deep neural networks lack

关键词： Homography estimation | Pixel-level SVDD | Gaussian density estimation | Correlation learning module

摘要： global calibration method based on an outlier removal | outlier removal mechanism enhances the accuracy of | High-accuracy calibration of uniaxial MEMS | -based systems is essential for achieving precise 3D | reconstructions because the calibration results will directly

关键词： Calibration | Outlier removal | Uniaxial MEMS | Fringe projection profilometry

摘要： improved the inter-beat interval (IBI) outlier* detection* | and removal* algorithm using the global-local context* | Consumer bearable technologies such as | earbttds are increasingly embedding physiological sensors | , including photo-plethysmography (PPG) and inertial

关键词： PPG | HRV | outlier removal | signal quality

摘要： registration (PCR). In this paper, we present a novel outlier | removal method, which locally corrects (LOCO) the | Finding reliable correspondences between two | point clouds is crucial for feature-based point cloud | initial correspondences to generate more correct

关键词： Point cloud compression | Training | Accuracy | Three-dimensional displays | Noise | Interference | Stability analysis

摘要： allows automatic removal* of outliers and does not* | As semiconductor process technology advances | , the runtimes of electronic design automation (EDA | ) jobs have become increasingly challenging. At the 3nm | process node, for example, a digital circuit design or

关键词： Industries | Schedules | Runtime | Accuracy | Training data | Reinforcement learning | Licenses | System-on-chip | Standards | Pragmatics

4008-161-200 800-990-8900

国家科技图书文献中心

摘要： outlier removal. By identifying and eliminating outliers | The EEGEyeNet dataset merges EEG data with eye | -tracking technology to advance cognitive research at the | intersection of brain dynamics and eye movement. By | developing machine learning models to predict eye movements

关键词： EEG | Gaze prediction | Machine learning | Vision transformer | EEGEyeNet | Data preprocessing

摘要： outlier removal on the radar data, and secondary | How to accurately acquire and track the | positions of multiple vehicles in a traffic system is a | challenging problem. Especially in the clustering detection | problem, the uncertainty of vehicle states (including

关键词： FMCW | Radar | Multi-target point cloud clustering | DBSCAN | Velocity-clustering | Multi-dimensional clustering fusion

摘要： techniques, such as missing value imputation, outlier | removal, and data normalization, were applied. The k | Seed classification, particularly for dry bean | seeds, is crucial for ensuring high agricultural | productivity and efficiency. This paper investigates the

关键词： Machine learning | Data analysis | Beans seed classification

摘要： thresholding method and Statistical Outlier Removal (SOR | This paper proposes an automatic road marking | extraction method based on vehicle-mounted laser scanning | data. First, the grid elevation difference threshold | method is used to segment the point cloud data into

关键词： Vehicle-mounted laser point cloud | Gridding | Intensity feature image | Road marking extraction

摘要： across each tunnel ring,followed by outlier removal | Shield tunneling construction is a predominant | method in metro infrastructure development,where the | wear of tunnel boring machine(TBM)cutters is a | critical issue that slows down its construction.The

关键词： Machine Learning | Cutter Wear Prediction | 1 D-Convolutional Neural Network

摘要： removal and mask generation. Specifically, we select | alignment as outlier detection. The pixel-level support | Homography estimation is a common image | alignment method. Existing methods of learning focused | principal plane masks through deep neural networks lack

关键词： Homography estimation | Pixel-level SVDD | Gaussian density estimation | Correlation learning module

摘要： global calibration method based on an outlier removal | outlier removal mechanism enhances the accuracy of | High-accuracy calibration of uniaxial MEMS | -based systems is essential for achieving precise 3D | reconstructions because the calibration results will directly

关键词： Calibration | Outlier removal | Uniaxial MEMS | Fringe projection profilometry

摘要： improved the inter-beat interval (IBI) outlier detection | and removal algorithm using the global-local context | Consumer bearable technologies such as | earbttds are increasingly embedding physiological sensors | , including photo-plethysmography (PPG) and inertial

关键词： PPG | HRV | outlier removal | signal quality

摘要： registration (PCR). In this paper, we present a novel outlier | removal method, which locally corrects (LOCO) the | Finding reliable correspondences between two | point clouds is crucial for feature-based point cloud | initial correspondences to generate more correct

关键词： Point cloud compression | Training | Accuracy | Three-dimensional displays | Noise | Interference | Stability analysis

摘要： allows automatic removal of outliers and does not | As semiconductor process technology advances | , the runtimes of electronic design automation (EDA | ) jobs have become increasingly challenging. At the 3nm | process node, for example, a digital circuit design or

关键词： Industries | Schedules | Runtime | Accuracy | Training data | Reinforcement learning | Licenses | System-on-chip | Standards | Pragmatics

4008-161-200 800-990-8900

国家科技图书文献中心

摘要： thresholding method and Statistical Outlier* Removal (SOR* | This paper proposes an automatic road marking | extraction method based on vehicle-mounted laser scanning | data. First, the grid elevation difference threshold | method is used to segment the point cloud data into

摘要： removal and mask generation. Specifically, we select | alignment as outlier* detection. The pixel-level support* | Homography estimation is a common image | alignment method. Existing methods of learning focused | principal plane masks through deep neural networks lack

摘要： improved the inter-beat interval (IBI) outlier* detection* | and removal* algorithm using the global-local context* | Consumer bearable technologies such as | earbttds are increasingly embedding physiological sensors | , including photo-plethysmography (PPG) and inertial

摘要： allows automatic removal* of outliers and does not* | As semiconductor process technology advances | , the runtimes of electronic design automation (EDA | ) jobs have become increasingly challenging. At the 3nm | process node, for example, a digital circuit design or