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Articles 1 - 5 of 5
Full-Text Articles in Electrical and Computer Engineering
Credit Card Fraud Detection, Charles Wang
Credit Card Fraud Detection, Charles Wang
Undergraduate Student Research Internships Conference
In recent years, credit card fraud poses a significant threat to banks and customers financially over the world. However, in the banking industry, to counter this issue, machine learning algorithms has become a growing trend to put proactive intervention of credit card fraud in place. In this project, we are going to detect fraudulent credit card transactions with machine learning models. This data set includes 284807 credit card transactions of European cardholders over a period of two days with their personal information kept anonymous. Among all transactions, 492 were fraudulent.
Globule Masks-Exact.Zip, Ananad K. Nambisan, Norsang Lama, Jason Hagerty, Colin Smith, Ahmad Rajeh, Thanh Phan, Samantha Swinfard, R. Joe Stanley
Globule Masks-Exact.Zip, Ananad K. Nambisan, Norsang Lama, Jason Hagerty, Colin Smith, Ahmad Rajeh, Thanh Phan, Samantha Swinfard, R. Joe Stanley
Deep Learning-based Dot and Globule Segmentation with Pixel and Blob-based Metrics for Evaluation – Data
No abstract provided.
Images.Zip, Ananad K. Nambisan, Norsang Lama, Jason Hagerty, Colin Smith, Ahmad Rajeh, Thanh Phan, Samantha Swinfard, R. Joe Stanley
Images.Zip, Ananad K. Nambisan, Norsang Lama, Jason Hagerty, Colin Smith, Ahmad Rajeh, Thanh Phan, Samantha Swinfard, R. Joe Stanley
Deep Learning-based Dot and Globule Segmentation with Pixel and Blob-based Metrics for Evaluation – Data
No abstract provided.
Globule Masks-Dilatedellipsekernel3.Zip, Ananad K. Nambisan, Norsang Lama, Jason Hagerty, Colin Smith, Ahmad Rajeh, Thanh Phan, Samantha Swinfard, R. Joe Stanley
Globule Masks-Dilatedellipsekernel3.Zip, Ananad K. Nambisan, Norsang Lama, Jason Hagerty, Colin Smith, Ahmad Rajeh, Thanh Phan, Samantha Swinfard, R. Joe Stanley
Deep Learning-based Dot and Globule Segmentation with Pixel and Blob-based Metrics for Evaluation – Data
No abstract provided.
Non-Contact Heart Rate Estimation In Low Snr Environments Using Mmwave Radar, Chandler J. Bauder, Aly E. Fathy
Non-Contact Heart Rate Estimation In Low Snr Environments Using Mmwave Radar, Chandler J. Bauder, Aly E. Fathy
Faculty Publications and Other Works -- EECS
Extracting accurate heart rate estimates of human subjects from a distance in high-noise scenarios using radar is a common problem. Often, frequency components from sources such as movement and vital signs from other subjects can overpower the weak reflected signal of the heart. In this study, we propose a signal processing scheme using a state-of-the-art Adaptive Multi-Trace Carving algorithm (AMTC) to accurately detect the heart rate signal over time in non-ideal scenarios. In our initial proof-of-concept results, we show a low heart rate estimation mean absolute error (MAE) of 3bpm for a single subject marching in place and less than …