62 citations · 81 across the 8 of their papers we have counts for
8 papers
Unsupervised Information Obfuscation for Split Inference of Neural Networks
Mohammad Samragh, Hossein Hosseini, Aleksei Triastcyn +3
Splitting network computations between the edge device and a server enables low edge-compute inference of neural networks but might expose sensitive information about the test quer…
Federated Learning of User Verification Models Without Sharing Embeddings
Hossein Hosseini, Hyunsin Park, Sungrack Yun +3
We consider the problem of training User Verification (UV) models in federated setting, where each user has access to the data of only one class and user embeddings cannot be share…
Federated Learning of User Authentication Models
Hossein Hosseini, Sungrack Yun, Hyunsin Park +3
Machine learning-based User Authentication (UA) models have been widely deployed in smart devices. UA models are trained to map input data of different users to highly separable em…
Real-Time Impulse Noise Suppression from Images Using an Efficient Weighted-Average Filtering
Hossein Hosseini, Farzad Hessar, Farokh Marvasti
In this paper, we propose a method for real-time high density impulse noise suppression from images. In our method, we first apply an impulse detector to identify the corrupted pix…
Image Block Loss Restoration Using Sparsity Pattern as Side Information
Hossein Hosseini, Ali Goli, Neda Barzegar Marvasti +2
In this paper, we propose a method for image block loss restoration based on the notion of sparse representation. We use the sparsity pattern as side information to efficiently res…
A GOST-like Blind Signature Scheme Based on Elliptic Curve Discrete Logarithm Problem
Hossein Hosseini, Behnam Bahrak, Farzad Hessar
In this paper, we propose a blind signature scheme and three practical educed schemes based on elliptic curve discrete logarithm problem. The proposed schemes impart the GOST signa…
Fast restoration of natural images corrupted by high-density impulse noise
Hossein Hosseini, Farokh Marvasti
In this paper, we suggest a general model for the fixed-valued impulse noise and propose a two-stage method for high density noise suppression while preserving the image details. I…
Image Inpainting Using Sparsity of the Transform Domain
H. Hosseini, N. B. Marvasti, F. Marvasti
In this paper, we propose a new image inpainting method based on the property that much of the image information in the transform domain is sparse. We add a redundancy to the origi…