Subject
- Biomedical Engineering 2
- Earth and Atmospheric Sciences 2
- Physics 2
- Agronomy 1
- Aviation Technology 1
- Computer Science 1
- Industrial Engineering 1
- Interdisciplinary Research 1
- Life Sciences 1
- Mechanical Engineering 1
Creator
- Pin-ching Li 2
- Sayan Dey, 0000-0002-5327-8431 2
- Venkatesh Mohan Merwade, 0000-0001-5518-2890 2
- Ahmed Khaled Soliman 1
- Aihua Huang 1
- Alexandre Zimmers 1
- Andres Torres 1
- Avnika Manaktala, 0000-0003-4470-4037 1
- Baichuan Zhang 1
- Bartlomiej P. Rajwa 1
Type
- Dataset 18
Date
subject: Machine Learning type: dataset
Total is 18 Results
Gait phase estimation using wearable sensors and PCA based linear regression model
10.4231/Q0HY-AT09
Ahmed Khaled Soliman
,
Andres Torres
,
Chang Heon Lee
,
Guilherme A. Ribeiro
,
Li-fan Wu
,
Mo Rastgaar
05/16/2022
Estimating gait realtime through 2 wearable sensors and a PCA based linear regression model.
Acceleration Biomedical Engineering Machine Learning Mechanical Engineering PCA Robotics Stepwise Multiple linear Regression Wearable Device
A Machine Learning Approach to Design of Aperiodic, Clustered-Dot Halftone Screens via Direct Binary Search
10.4231/AMGQ-0T59
Itamar Roth
,
Jan Allebach
,
Jiayin Liu
,
Orel Bat Mor
,
Oren Haik
,
Shani Gat
,
Tal Frank
,
Yitzhak Yitzhaky
06/01/2022
This dataset contains two parts: one has halftone patches that were used to predicts the quality level and scale using machine learning methods. The second part contains full versions of halftone images so viewers can zoom in to see the details.
direct binary search Electrical and Computer Engineering Halftone screen Machine Learning
Data for Characterization of Acoustic Emissions from Analogue Rocks using Sparse Regression-DMDc
10.4231/4K64-4818
Charles Fieseler
,
Chven Mitchell
,
Laura J Pyrak-Nolte
,
Nathan Kutz
06/14/2022
Acoustic waveforms collected during the monitoring of moisture loss in synthetic rock samples composed of mortar, and mortar with either distributed clay or localized clay, under ambient laboratory conditions.
acoustic signals clay cracking Fractures Machine Learning Physics
Clustering in Machine Learning Pattern Formation of VO2
10.4231/966Q-6F95
Alexandre Zimmers
,
Dmitri Basov
,
Erica Carlson
,
Forrest Simmons
,
Ivan K. Schuller
,
Lionel Aigouy
,
Lukasz Burzawa
,
Melissa Alzate Banguero
,
Mumtaz Qazilbash
,
Pavel Salev
,
Sayan Basak
04/07/2023
Codes used in "Deep Learning Hamiltonians form Disordered Image Data in Quantum Materials" https://arxiv.org/abs/2211.01490 and the resulting visualizations.
Clustering Machine Learning Physics quantum materials Scientific visualization symmetry Vanadium dioxide VO2
Genome-wide, Organ-delimited gene regulatory networks (OD-GRN) provide high accuracy in candidate Transcription Factor (TF) selection across diverse processes
10.4231/50R5-EM83
Karen Hudson
,
Kranthi K Varala
,
Ying Li
01/04/2024
Organ-specific gene expression datasets that include hundreds to thousands of experiments allow reconstruction of gene regulatory networks and discovery of transcriptional regulators various pathways and processes.
Arabidopsis thaliana Gene regulatory networks k-nearest neighbor (kNN) linear support vector machines (SVM) Machine Learning Systems biology
Modeling the Sea Level Changes in Guam
10.4231/0A0F-7A84
10/14/2019
This project works on understanding the different statistical models that are available to analyze and predict mean sea level changes in Guam.
Climate Change Data Education Earth and Atmospheric Sciences FAIR Data Machine Learning Sea level rise Statistical analysis Statistical Methods
Data of global wetland methane emissions from artificial neural network modeling v1.0
10.4231/3YX4-EY30
01/21/2020
Source code of an ANN model, site level data, input data, output data and visualization results, which are presented in the manuscript "Inventorying Global Wetland Methane Emissions Based on In Situ Data and an Artificial Neural Network...
Artificial Neural Network (ANN) Atmospheric Chemistry Modeling Biogeochemistry Earth and Atmospheric Sciences Interactive Data Language (IDL) Machine Learning Matlab Methane Dynamics Model (MDM) Methane Emission
Code and Dataset for TARP Detection Benchmarks
10.4231/R7ST7MVC
Kelsie Larson
,
Mireille Boutin
05/16/2017
The TARP method uses random projections, followed by threshold classifications, to construct receiver-operating characteristic curves and uncover underlying structure in the given data.
Electrical and Computer Engineering Machine Learning Receiver Operating Characteristics ROC curve Signal Processing Target Detection
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