Search Results for author: Mozhdeh Rouhsedaghat

Found 7 papers, 2 papers with code

MAGIC: Mask-Guided Image Synthesis by Inverting a Quasi-Robust Classifier

1 code implementation23 Sep 2022 Mozhdeh Rouhsedaghat, Masoud Monajatipoor, Kai-Wei Chang, C. -C. Jay Kuo, Iacopo Masi

We offer a method for one-shot image synthesis that allows controlling manipulations of a single image by inverting a quasi-robust classifier equipped with strong regularizers.

Image Generation

Successive Subspace Learning: An Overview

no code implementations27 Feb 2021 Mozhdeh Rouhsedaghat, Masoud Monajatipoor, Zohreh Azizi, C. -C. Jay Kuo

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 in point cloud sets).

Low-Resolution Face Recognition In Resource-Constrained Environments

no code implementations23 Nov 2020 Mozhdeh Rouhsedaghat, Yifan Wang, Shuowen Hu, Suya You, C. -C. Jay Kuo

A non-parametric low-resolution face recognition model for resource-constrained environments with limited networking and computing is proposed in this work.

Active Learning Face Recognition

FaceHop: A Light-Weight Low-Resolution Face Gender Classification Method

no code implementations18 Jul 2020 Mozhdeh Rouhsedaghat, Yifan Wang, Xiou Ge, Shuowen Hu, Suya You, C. -C. Jay Kuo

For gray-scale face images of resolution $32 \times 32$ in the LFW and the CMU Multi-PIE datasets, FaceHop achieves correct gender classification rates of 94. 63% and 95. 12% with model sizes of 16. 9K and 17. 6K parameters, respectively.

Classification General Classification

PixelHop++: A Small Successive-Subspace-Learning-Based (SSL-based) Model for Image Classification

no code implementations8 Feb 2020 Yueru Chen, Mozhdeh Rouhsedaghat, Suya You, Raghuveer Rao, C. -C. Jay Kuo

In PixelHop++, one can control the learning model size of fine-granularity, offering a flexible tradeoff between the model size and the classification performance.

Classification General Classification +1

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