most citedDenosing Using Wavelets and Projections onto the L1-Ball

4 citations · 5 across the 3 of their papers we have counts for

collaborators

6 papers

cs.CV20193 cited

An Algorithm Unrolling Approach to Deep Image Deblurring

Yuelong Li, Mohammad Tofighi, Vishal Monga +1

While neural networks have achieved vastly enhanced performance over traditional iterative methods in many cases, they are generally empirically designed and the underlying structu…

eess.IV201916 cited

Deep Algorithm Unrolling for Blind Image Deblurring

Yuelong Li, Mohammad Tofighi, Junyi Geng +2

Blind image deblurring remains a topic of enduring interest. Learning based approaches, especially those that employ neural networks have emerged to complement traditional model ba…

eess.IV2019

Prior Information Guided Regularized Deep Learning for Cell Nucleus Detection

Mohammad Tofighi, Tiantong Guo, Jairam K. P. Vanamala +1

Cell nuclei detection is a challenging research topic because of limitations in cellular image quality and diversity of nuclear morphology, i.e. varying nuclei shapes, sizes, and o…

math.OC20144 cited

Denosing Using Wavelets and Projections onto the L1-Ball

A. Enis Cetin, Mohammad Tofighi

Both wavelet denoising and denosing methods using the concept of sparsity are based on soft-thresholding. In sparsity based denoising methods, it is assumed that the original signa…

cs.CV20121 cited

Robust Head Pose Estimation Using Contourlet Transform

Mohammad Tofighi, Hashem Kalbkhani, Mahrokh G. Shayesteh +1

Estimating pose of the head is an important preprocessing step in many pattern recognition and computer vision systems such as face recognition. Since the performance of the face r…

cs.CV2012

Compensating Interpolation Distortion by Using New Optimized Modular Method

Mohammad Tofighi, Ali Ayremlou, Farokh Marvasti

A modular method was suggested before to recover a band limited signal from the sample and hold and linearly interpolated (or, in general, an nth-order-hold) version of the regular…