398 citations · 413 across the 14 of their papers we have counts for
14 papers
Generation of Synthetic Fingerphotos with GANs
Conor Miller-Lynch, Sandip Purnapatra, Syed Konain Abbas +4
Contactless fingerprinting is an emerging approach to biometric authentication that allows users to scan their fingerprints without touching a scanner. Due to the limited amount of…
Adoption-Ready Project-Based Learning for Computing Education: The FORAP Framework and a Multi-Scale Project Portfolio
Ahmad D. Suleiman, Jan DeWaters, David C. Shepherd +4
This innovative practice full paper presents FORAP (Framework for Organizing Reusable and Adaptable PjBL Projects) and a portfolio of 14 adoption-ready project-based learning (PjBL…
Explainable Face Presentation Attack Detection via Ensemble-CAM
Rashik Shadman, M G Sarwar Murshed, Faraz Hussain
Presentation attacks represent a critical security threat where adversaries use fake biometric data, such as face, fingerprint, or iris images, to gain unauthorized access to prote…
Conditional Synthetic Live and Spoof Fingerprint Generation
Syed Konain Abbas, Sandip Purnapatra, M. G. Sarwar Murshed +5
Large fingerprint datasets, while important for training and evaluation, are time-consuming and expensive to collect and require strict privacy measures. Researchers are exploring…
Explainable Face Recognition via Improved Localization
Rashik Shadman, Daqing Hou, Faraz Hussain +1
Biometric authentication has become one of the most widely used tools in the current technological era to authenticate users and to distinguish between genuine users and imposters.…
Deep Learning-Based Approaches for Contactless Fingerprints Segmentation and Extraction
M. G. Sarwar Murshed, Syed Konain Abbas, Sandip Purnapatra +2
Fingerprints are widely recognized as one of the most unique and reliable characteristics of human identity. Most modern fingerprint authentication systems rely on contact-based fi…
Deep Age-Invariant Fingerprint Segmentation System
M. G. Sarwar Murshed, Keivan Bahmani, Stephanie Schuckers +1
Fingerprint-based identification systems achieve higher accuracy when a slap containing multiple fingerprints of a subject is used instead of a single fingerprint. However, segment…
Deep Slap Fingerprint Segmentation for Juveniles and Adults
M. G. Sarwar Murshed, Robert Kline, Keivan Bahmani +2
Many fingerprint recognition systems capture four fingerprints in one image. In such systems, the fingerprint processing pipeline must first segment each four-fingerprint slap into…
Pulmonary Disease Classification Using Globally Correlated Maximum Likelihood: an Auxiliary Attention mechanism for Convolutional Neural Networks
Edward Verenich, Tobias Martin, Alvaro Velasquez +2
Convolutional neural networks (CNN) are now being widely used for classifying and detecting pulmonary abnormalities in chest radiographs. Two complementary generalization propertie…
Improving Explainability of Image Classification in Scenarios with Class Overlap: Application to COVID-19 and Pneumonia
Edward Verenich, Alvaro Velasquez, Nazar Khan +1
Trust in predictions made by machine learning models is increased if the model generalizes well on previously unseen samples and when inference is accompanied by cogent explanation…
The Utility of Feature Reuse: Transfer Learning in Data-Starved Regimes
Rashik Shadman, M. G. Sarwar Murshed, Edward Verenich +2
The use of transfer learning with deep neural networks has increasingly become widespread for deploying well-tested computer vision systems to newer domains, especially those with…
Hazard Detection in Supermarkets using Deep Learning on the Edge
M. G. Sarwar Murshed, Edward Verenich, James J. Carroll +2
Supermarkets need to ensure clean and safe environments for both shoppers and employees. Slips, trips, and falls can result in injuries that have a physical as well as financial co…
FlexServe: Deployment of PyTorch Models as Flexible REST Endpoints
Edward Verenich, Alvaro Velasquez, M. G. Sarwar Murshed +1
The integration of artificial intelligence capabilities into modern software systems is increasingly being simplified through the use of cloud-based machine learning services and r…
Machine Learning at the Network Edge: A Survey
M. G. Sarwar Murshed, Christopher Murphy, Daqing Hou +3
Resource-constrained IoT devices, such as sensors and actuators, have become ubiquitous in recent years. This has led to the generation of large quantities of data in real-time, wh…