10 citations · 28 across the 11 of their papers we have counts for
11 papers
3D Neuron Morphology Analysis
Jiaxiang Jiang, Michael Goebel, Cezar Borba +2
We consider the problem of finding an accurate representation of neuron shapes, extracting sub-cellular features, and classifying neurons based on neuron shapes. In neuroscience re…
Generalizable Deepfake Detection with Phase-Based Motion Analysis
Ekta Prashnani, Michael Goebel, B. S. Manjunath
We propose PhaseForensics, a DeepFake (DF) video detection method that leverages a phase-based motion representation of facial temporal dynamics. Existing methods relying on tempor…
Deep Learning Enabled Time-Lapse 3D Cell Analysis
Jiaxiang Jiang, Amil Khan, S. Shailja +4
This paper presents a method for time-lapse 3D cell analysis. Specifically, we consider the problem of accurately localizing and quantitatively analyzing sub-cellular features, and…
LECA: A Learned Approach for Efficient Cover-agnostic Watermarking
Xiyang Luo, Michael Goebel, Elnaz Barshan +1
In this work, we present an efficient multi-bit deep image watermarking method that is cover-agnostic yet also robust to geometric distortions such as translation and scaling as we…
Holistic Image Manipulation Detection using Pixel Co-occurrence Matrices
Lakshmanan Nataraj, Michael Goebel, Tajuddin Manhar Mohammed +2
Digital image forensics aims to detect images that have been digitally manipulated. Realistic image forgeries involve a combination of splicing, resampling, region removal, smoothi…
Attribution of Gradient Based Adversarial Attacks for Reverse Engineering of Deceptions
Michael Goebel, Jason Bunk, Srinjoy Chattopadhyay +3
Machine Learning (ML) algorithms are susceptible to adversarial attacks and deception both during training and deployment. Automatic reverse engineering of the toolchains behind th…
StressNet: Detecting Stress in Thermal Videos
Satish Kumar, A S M Iftekhar, Michael Goebel +7
Precise measurement of physiological signals is critical for the effective monitoring of human vital signs. Recent developments in computer vision have demonstrated that signals su…
Adversarial Attacks on Co-Occurrence Features for GAN Detection
Michael Goebel, B. S. Manjunath
Improvements in Generative Adversarial Networks (GANs) have greatly reduced the difficulty of producing new, photo-realistic images with unique semantic meaning. With this rise in…
Detection, Attribution and Localization of GAN Generated Images
Michael Goebel, Lakshmanan Nataraj, Tejaswi Nanjundaswamy +3
Recent advances in Generative Adversarial Networks (GANs) have led to the creation of realistic-looking digital images that pose a major challenge to their detection by humans or c…
Predicting Fluid Intelligence of Children using T1-weighted MR Images and a StackNet
Po-Yu Kao, Angela Zhang, Michael Goebel +2
In this work, we utilize T1-weighted MR images and StackNet to predict fluid intelligence in adolescents. Our framework includes feature extraction, feature normalization, feature…
Deep Learning Methods for Event Verification and Image Repurposing Detection
M. Goebel, A. Flenner, L. Nataraj +1
The authenticity of images posted on social media is an issue of growing concern. Many algorithms have been developed to detect manipulated images, but few have investigated the ab…