most citedConfidence Aware Neural Networks for Skin Cancer Detection

8 citations · 9 across the 3 of their papers we have counts for

collaborators

6 papers

eess.IV20218 cited

Confidence Aware Neural Networks for Skin Cancer Detection

Donya Khaledyan, AmirReza Tajally, Ali Sarkhosh +4

Deep learning (DL) models have received particular attention in medical imaging due to their promising pattern recognition capabilities. However, Deep Neural Networks (DNNs) requir…

eess.IV2020

A practical method for pupil segmentation in challenging conditions

Donya Khaledyan, Mohammad Eshghi, Morteza Heidari +2

Various methods have been proposed for authentication, including password or pattern drawing, which is clearly visible on personal electronic devices. However, these methods of aut…

eess.IV2020

Image quality enhancement in wireless capsule endoscopy with adaptive fraction gamma transformation and unsharp masking filter

Rezvan Ezatian, Donya Khaledyan, Kian Jafari +3

Wireless Capsule Endoscopy (WCE) presented in 2001 as one of the key approaches to observe the entire gastrointestinal (GI) tract, generally the small bowels. It has been used to d…

eess.IV20201 cited

Low-Cost Implementation of Bilinear and Bicubic Image Interpolation for Real-Time Image Super-Resolution

Donya Khaledyan, Abdolah Amirany, Kian Jafari +3

Super-resolution imaging (S.R.) is a series of techniques that enhance the resolution of an imaging system, especially in surveillance cameras where simplicity and low cost are of…

eess.IV2020

Deep learning denoising for EOG artifacts removal from EEG signals

Najmeh Mashhadi, Abolfazl Zargari Khuzani, Morteza Heidari +1

There are many sources of interference encountered in the electroencephalogram (EEG) recordings, specifically ocular, muscular, and cardiac artifacts. Rejection of EEG artifacts is…

cs.CV2020

An approach to human iris recognition using quantitative analysis of image features and machine learning

Abolfazl Zargari Khuzani, Najmeh Mashhadi, Morteza Heidari +1

The Iris pattern is a unique biological feature for each individual, making it a valuable and powerful tool for human identification. In this paper, an efficient framework for iris…