14 citations · 31 across the 4 of their papers we have counts for
6 papers
BERTHop: An Effective Vision-and-Language Model for Chest X-ray Disease Diagnosis
Masoud Monajatipoor, Mozhdeh Rouhsedaghat, Liunian Harold Li +4
Vision-and-language(V&L) models take image and text as input and learn to capture the associations between them. Prior studies show that pre-trained V&L models can significantly im…
DefakeHop: A Light-Weight High-Performance Deepfake Detector
Hong-Shuo Chen, Mozhdeh Rouhsedaghat, Hamza Ghani +3
A light-weight high-performance Deepfake detection method, called DefakeHop, is proposed in this work. State-of-the-art Deepfake detection methods are built upon deep neural networ…
Successive Subspace Learning: An Overview
Mozhdeh Rouhsedaghat, Masoud Monajatipoor, Zohreh Azizi +1
Successive Subspace Learning (SSL) offers a light-weight unsupervised feature learning method based on inherent statistical properties of data units (e.g. image pixels and points i…
Low-Resolution Face Recognition In Resource-Constrained Environments
Mozhdeh Rouhsedaghat, Yifan Wang, Shuowen Hu +2
A non-parametric low-resolution face recognition model for resource-constrained environments with limited networking and computing is proposed in this work. Such environments often…
FaceHop: A Light-Weight Low-Resolution Face Gender Classification Method
Mozhdeh Rouhsedaghat, Yifan Wang, Xiou Ge +3
A light-weight low-resolution face gender classification method, called FaceHop, is proposed in this research. We have witnessed rapid progress in face gender classification accura…
PixelHop++: A Small Successive-Subspace-Learning-Based (SSL-based) Model for Image Classification
Yueru Chen, Mozhdeh Rouhsedaghat, Suya You +2
The successive subspace learning (SSL) principle was developed and used to design an interpretable learning model, known as the PixelHop method,for image classification in our prio…