Datasets

Subject
Creator
Type
Date

subject: Machine Learning

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

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.

ADS-B Aviation Technology Clustering Machine Learning

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

Data for Analyzing the Effect of Data Splitting and Covariate Shift on Machine Leaning Based Streamflow Prediction in Ungauged Basins

10.4231/0PG5-KC30

Pin-ching Li, Sayan Dey, 0000-0002-5327-8431, Venkatesh Mohan Merwade, 0000-0001-5518-2890

01/23/2023

This resource contains the data used in the study "Analyzing the Effect of Data Splitting and Covariate Shift on Machine Leaning Based Streamflow Prediction in Ungauged Basins" published in Water Resources Research (doi: 10.1029/2023WR034464)

Artificial Neural Network (ANN) covariate shift Hydrology Machine Learning prediction in ungauged basin Random Forest streamflow prediction

Codes for Analyzing the Effect of Data Splitting and Covariate Shift on Machine Leaning Based Streamflow Prediction in Ungauged Basins

10.4231/B783-2C47

Pin-ching Li, Sayan Dey, 0000-0002-5327-8431, Venkatesh Mohan Merwade, 0000-0001-5518-2890

01/23/2023

This resource contains codes used in the study "Analyzing the Effect of Data Splitting and Covariate Shift on Machine Leaning Based Streamflow Prediction in Ungauged Basins" published in Water Resources Research (doi: 10.1029/2023WR034464)

Artificial Neural Network (ANN) Machine Learning Random Forest streamflow prediction

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

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, 0000-0001-5630-6824, 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

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