activity
20172025
most citedSmart Augmentation - Learning an Optimal Data Augmentation Strategy

439 citations · 472 across the 5 of their papers we have counts for

collaborators

6 papers

cs.CV2025

Contactless Cardiac Pulse Monitoring Using Event Cameras

Mohamed Moustafa, Joseph Lemley, Peter Corcoran

Time event cameras are a novel technology for recording scene information at extremely low latency and with low power consumption. Event cameras output a stream of events that enca…

cs.CV2024

Synthetic Face Ageing: Evaluation, Analysis and Facilitation of Age-Robust Facial Recognition Algorithms

Wang Yao, Muhammad Ali Farooq, Joseph Lemley +1

The ability to accurately recognize an individual's face with respect to human aging factor holds significant importance for various private as well as government sectors such as c…

cs.CV2023

A Comparative Study of Image-to-Image Translation Using GANs for Synthetic Child Race Data

Wang Yao, Muhammad Ali Farooq, Joseph Lemley +1

The lack of ethnic diversity in data has been a limiting factor of face recognition techniques in the literature. This is particularly the case for children where data samples are…

cs.CV2018★ 12 cited

Efficient CNN Implementation for Eye-Gaze Estimation on Low-Power/Low-Quality Consumer Imaging Systems

Joseph Lemley, Anuradha Kar, Alexandru Drimbarean +1

Accurate and efficient eye gaze estimation is important for emerging consumer electronic systems such as driver monitoring systems and novel user interfaces. Such systems are requi…

cs.CG2017★ 21 cited

Big Holes in Big Data: A Monte Carlo Algorithm for Detecting Large Hyper-rectangles in High Dimensional Data

Joseph Lemley, Filip Jagodzinski, Razvan Andonie

We present the first algorithm for finding holes in high dimensional data that runs in polynomial time with respect to the number of dimensions. Previous algorithms are exponential…

cs.AI2017★ 439 cited

Smart Augmentation - Learning an Optimal Data Augmentation Strategy

Joseph Lemley, Shabab Bazrafkan, Peter Corcoran

A recurring problem faced when training neural networks is that there is typically not enough data to maximize the generalization capability of deep neural networks(DNN). There are…