2 citations · 4 across the 8 of their papers we have counts for
9 papers
Engineering deep learning methods on automatic detection of damage in infrastructure due to extreme events
Yongsheng Bai, Bing Zha, Halil Sezen +1
This paper presents a few comprehensive experimental studies for automated Structural Damage Detection (SDD) in extreme events using deep learning methods for processing 2D images.…
Network Comparison Study of Deep Activation Feature Discriminability with Novel Objects
Michael Karnes, Alper Yilmaz
Feature extraction has always been a critical component of the computer vision field. More recently, state-of-the-art computer visions algorithms have incorporated Deep Neural Netw…
Automatic Displacement and Vibration Measurement in Laboratory Experiments with A Deep Learning Method
Yongsheng Bai, Ramzi M. Abduallah, Halil Sezen +1
This paper proposes a pipeline to automatically track and measure displacement and vibration of structural specimens during laboratory experiments. The latest Mask Regional Convolu…
Adaptive Few-Shot Learning PoC Ultrasound COVID-19 Diagnostic System
Michael Karnes, Shehan Perera, Srikar Adhikari +1
This paper presents a novel ultrasound imaging point-of-care (PoC) COVID-19 diagnostic system. The adaptive visual diagnostics utilize few-shot learning (FSL) to generate encoded d…
A volumetric change detection framework using UAV oblique photogrammetry - A case study of ultra-high-resolution monitoring of progressive building collapse
Ningli Xu, Debao Huang, Shuang Song +5
In this paper, we present a case study that performs an unmanned aerial vehicle (UAV) based fine-scale 3D change detection and monitoring of progressive collapse performance of a b…
POCFormer: A Lightweight Transformer Architecture for Detection of COVID-19 Using Point of Care Ultrasound
Shehan Perera, Srikar Adhikari, Alper Yilmaz
The rapid and seemingly endless expansion of COVID-19 can be traced back to the inefficiency and shortage of testing kits that offer accurate results in a timely manner. An emergin…