34 citations · 56 across the 10 of their papers we have counts for
10 papers
Device Image-IV Mapping using Variational Autoencoder for Inverse Design and Forward Prediction
Thomas Lu, Albert Lu, Hiu Yung Wong
This paper demonstrates the learning of the underlying device physics by mapping device structure images to their corresponding Current-Voltage (IV) characteristics using a novel f…
Neurosymbolic hybrid approach to driver collision warning
Kyongsik Yun, Thomas Lu, Alexander Huyen +2
There are two main algorithmic approaches to autonomous driving systems: (1) An end-to-end system in which a single deep neural network learns to map sensory input directly into ap…
Explainability Tools Enabling Deep Learning in Future In-Situ Real-Time Planetary Explorations
Daniel Lundstrom, Alexander Huyen, Arya Mevada +2
Deep learning (DL) has proven to be an effective machine learning and computer vision technique. DL-based image segmentation, object recognition and classification will aid many in…
Transforming unstructured voice and text data into insight for paramedic emergency service using recurrent and convolutional neural networks
Kyongsik Yun, Thomas Lu, Alexander Huyen
Paramedics often have to make lifesaving decisions within a limited time in an ambulance. They sometimes ask the doctor for additional medical instructions, during which valuable t…
Improved visible to IR image transformation using synthetic data augmentation with cycle-consistent adversarial networks
Kyongsik Yun, Kevin Yu, Joseph Osborne +4
Infrared (IR) images are essential to improve the visibility of dark or camouflaged objects. Object recognition and segmentation based on a neural network using IR images provide m…
Small Target Detection for Search and Rescue Operations using Distributed Deep Learning and Synthetic Data Generation
Kyongsik Yun, Luan Nguyen, Tuan Nguyen +5
It is important to find the target as soon as possible for search and rescue operations. Surveillance camera systems and unmanned aerial vehicles (UAVs) are used to support search…