subject: Machine Learning

Total is 12 Results
Simplicity of K-means versus deepness of Deep Learning. A Case of Unsupervised Feature Learning with Limited Data


Baichuan Zhang, Bartlomiej P. Rajwa, Murat Dundar, Qiang Kou, Yicheng He


We study a biodetection application as a case study to demonstrate that K-means-based unsupervised feature learning can be a simple yet effective alternative to deep learning techniques for small data sets with limited intra- as well as inter-class diversi...

bacterial colonies BARDOT Biomedical Engineering Computer Science deep learning Elastic light scattering Interdisciplinary Research K-Means Clustering Life Sciences Machine Learning representation learning

Modeling the Sea Level Changes in Guam


Avnika Manaktala


This project was created to act as a final project submission for the EAPS591 course Cybertraining for FAIR Data Science offered by Purdue University for the Fall 2019-2020 semester. The aim of this project is to create a workflow for analysis and modeling...

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


Licheng Liu, Qianlai Zhuang


Methane (CH4) emissions from wetland ecosystems exert large positive feedbacks to the global climate system. However, the estimation of wetland CH4 emissions at the global scale still has large uncertainties. Here we develop a predictive model of CH4 emiss...

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


Kelsie Larson, Mireille Boutin


This is the code for constructing the Thresholding After Random Projection (TARP) benchmark for a detection problem using labeled data. The benchmark is a curve in a two-dimensional plane whose x-axis is the Area Above the ROC Curve (AAC) and whose y-axis...

Electrical and Computer Engineering Machine Learning Receiver Operating Characteristics ROC curve Signal Processing Target Detection

Structural attributes derived from Google Street View imagery, Louisiana coastal zone


David R Johnson, Ed Delp, Fu-Chen Chen, Mohammad Jahanshahi


When developing plans for flood risk mitigation, one of the first hurdles local and state regional decision-makers must clear is gathering data on what assets actually exist on the ground in their jurisdictions. Even in areas like Louisiana—where significa...

flood risk Industrial Engineering Machine Learning structure attributes

Evaluating Economic Opportunities for Product Recycling via the Sherwood Principle and Machine Learning - Supporting Information


Aihua Huang, John W. Sutherland, Sidi Deng, Xiaoyu Zhou, Yuehwern Yih


This study proposes an empirical model to identify economic feasibility of product recycling by integrating machine learning and the Sherwood principle. A boundary that differentiates profitable and non-profitable EoL products for material recycling is qua...

Circular Economy Empirical Models Environmental and Ecological Engineering Machine Learning Sherwood Principle

General Aviation Flight Phase Identification using Automatic Dependent Surveillance-Broadcast (ADS-B)


John H Mott, Qilei Zhang


The dataset consists of data from August 17, 2020, received by the ADS-B equipment installed at the Purdue University Airport (KLAF). The FAA aircraft registration database is also provided to assist in merging with the ADS-B data using the hex identificat...

ADS-B Aviation Technology Clustering Machine Learning

RoboMal Malware Detection Dataset


Byung-cheol Min, Haozhe Zhou, Richard Voyles, Upinder Kaur, Xiaxin Shen


RoboMal dataset is a collection of binary executables (ELF files) that are used to train and test machine learning models for malware detection in robotic software. All samples are labeled and the labels are provided in the CSV file. The RoboMal framework...

Engineering Technology Machine Learning malware Python Robotics security

Multi-Species Prediction of Physiological Traits with Hyper-Spectral Modeling


Meng-yang Lin, Mitchell R Tuinstra


Lack of high-throughput phenotyping is a bottleneck to breeding for abiotic stress tolerance in crop plants. Efficient and non-destructive hyperspectral imaging can quantify plant physiological traits under abiotic stresses; however, prediction models gene...

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


Ahmed Khaled Soliman, Andres Torres, Chang Heon Lee, Guilherme A. Ribeiro, Li-fan Wu, Mo Rastgaar


Human gait analysis and detection are critical for many applications including wearable robotic devices, rehabilitation robots, reducing or tracking injury risk. We present an experimental protocol to label gait events based on gait patterns of human subje...

Acceleration Biomedical Engineering Machine Learning Mechanical Engineering PCA Robotics Stepwise Multiple linear Regression Wearable Device

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