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 16
Date
Total is 16 Results
Simplicity of K-means versus deepness of Deep Learning. A Case of Unsupervised Feature Learning with Limited Data
10.4231/R7N58J9Z
Baichuan Zhang, Bartlomiej P. Rajwa, Murat Dundar, Qiang Kou, Yicheng He
10/01/2015
A study contrasting K-means-based unsupervised feature learning and deep learning techniques for small data sets with limited intra- as well as inter-class diversity
bacterial colonies BARDOT Biomedical Engineering Computer Science deep learning Elastic light scattering Interdisciplinary Research K-Means Clustering Life Sciences Machine Learning representation learning
Structural attributes derived from Google Street View imagery, Louisiana coastal zone
10.4231/1TZX-BR43
David R Johnson, 0000-0002-2364-340X, Ed Delp, 0000-0002-2909-7323, Fu-Chen Chen, 0000-0002-6396-2798, Mohammad Jahanshahi
07/28/2020
Structural attributes relevant to flood risk (foundation height/type, square footage, number of stories, building type), produced using machine learning for automated image analysis of GSV images.
flood risk Industrial Engineering Machine Learning structure attributes
Evaluating Economic Opportunities for Product Recycling via the Sherwood Principle and Machine Learning - Supporting Information
10.4231/E80W-7941
Aihua Huang, John W. Sutherland, 0000-0002-2118-0907, Sidi Deng, 0009-0003-9234-1952, Xiaoyu Zhou, 0000-0002-5083-1713, Yuehwern Yih, 0000-0003-2087-7718
09/03/2020
This repository contains the supporting information for the manuscript regarding Sherwood principle and Machine learning. All critical underlying data files, along with a flow chart that describes the methodologies applied in the paper are enclosed.
Circular Economy Empirical Models Environmental and Ecological Engineering Machine Learning Sherwood Principle
Modeling the Sea Level Changes in Guam
10.4231/0A0F-7A84
Avnika Manaktala, 0000-0003-4470-4037
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
Licheng Liu, 0000-0002-9649-1056, Qianlai Zhuang, 0000-0002-4536-9851
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, 0000-0002-0837-6577
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
General Aviation Flight Phase Identification using Automatic Dependent Surveillance-Broadcast (ADS-B)
10.4231/X0HZ-MF23
John H Mott, Qilei Zhang, 0000-0003-1364-9661
08/23/2021
Dataset including KLAF ADS-B data and synthetic flight data for clustering validation purposes.
RoboMal Malware Detection Dataset
10.4231/YN7G-H807
Byung-cheol Min, 0000-0001-6458-4365, Haozhe Zhou, Richard Voyles, Upinder Kaur, 0000-0002-5576-1777, Xiaxin Shen
10/15/2021
The RoboMal Dataset consists of 450 binary executables designed to facilitate malware detection in robotic software.
Engineering Technology Machine Learning malware Python Robotics security
Multi-Species Prediction of Physiological Traits with Hyper-Spectral Modeling
10.4231/FPHP-0153
Meng-yang Lin, Mitchell R Tuinstra, 0000-0002-5322-6519
02/11/2022
High-throughput hyperspectral imaging in corn and sorghum can be used in multi-species models to predict water and nitrogen status of plants within and across these crop species.
Abiotic stress Agronomy Corn Ecophysiology High-throughput Phenotyping Machine Learning nitrogen content partial least square regression relative water content Remote Sensing Sorghum
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, 0000-0003-4638-3345
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
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