25 citations · 70 across the 16 of their papers we have counts for
19 papers
Extended Few-Shot Learning: Exploiting Existing Resources for Novel Tasks
Reza Esfandiarpoor, Amy Pu, Mohsen Hajabdollahi +1
In many practical few-shot learning problems, even though labeled examples are scarce, there are abundant auxiliary datasets that potentially contain useful information. We propose…
Classification of Diabetic Retinopathy Using Unlabeled Data and Knowledge Distillation
Sajjad Abbasi, Mohsen Hajabdollahi, Pejman Khadivi +4
Knowledge distillation allows transferring knowledge from a pre-trained model to another. However, it suffers from limitations, and constraints related to the two models need to be…
Hardware Implementation of Adaptive Watermarking Based on Local Spatial Disorder Analysis
Mohsen Hajabdolahi, Nader Karimi, Shahram Shirani +1
With the increasing use of the internet and the ease of exchange of multimedia content, the protection of ownership rights has become a significant concern. Watermarking is an effi…
Acceleration of Convolutional Neural Network Using FFT-Based Split Convolutions
Kamran Chitsaz, Mohsen Hajabdollahi, Nader Karimi +2
Convolutional neural networks (CNNs) have a large number of variables and hence suffer from a complexity problem for their implementation. Different methods and techniques have dev…
Unlabeled Data Deployment for Classification of Diabetic Retinopathy Images Using Knowledge Transfer
Sajjad Abbasi, Mohsen Hajabdollahi, Nader Karimi +2
Convolutional neural networks (CNNs) are extensively beneficial for medical image processing. Medical images are plentiful, but there is a lack of annotated data. Transfer learning…
Splitting Convolutional Neural Network Structures for Efficient Inference
Emad MalekHosseini, Mohsen Hajabdollahi, Nader Karimi +2
For convolutional neural networks (CNNs) that have a large volume of input data, memory management becomes a major concern. Memory cost reduction can be an effective way to deal wi…
Convolutional Neural Network Pruning Using Filter Attenuation
Morteza Mousa-Pasandi, Mohsen Hajabdollahi, Nader Karimi +2
Filters are the essential elements in convolutional neural networks (CNNs). Filters are corresponded to the feature maps and form the main part of the computational and memory requ…
Modeling of Pruning Techniques for Deep Neural Networks Simplification
Morteza Mousa Pasandi, Mohsen Hajabdollahi, Nader Karimi +1
Convolutional Neural Networks (CNNs) suffer from different issues, such as computational complexity and the number of parameters. In recent years pruning techniques are employed to…
Modeling Neural Architecture Search Methods for Deep Networks
Emad Malekhosseini, Mohsen Hajabdollahi, Nader Karimi +1
There are many research works on the designing of architectures for the deep neural networks (DNN), which are named neural architecture search (NAS) methods. Although there are man…
Modeling Teacher-Student Techniques in Deep Neural Networks for Knowledge Distillation
Sajjad Abbasi, Mohsen Hajabdollahi, Nader Karimi +1
Knowledge distillation (KD) is a new method for transferring knowledge of a structure under training to another one. The typical application of KD is in the form of learning a smal…
Multiple Abnormality Detection for Automatic Medical Image Diagnosis Using Bifurcated Convolutional Neural Network
Mohsen Hajabdollahi, Reza Esfandiarpoor, Elyas Sabeti +4
Automating classification and segmentation process of abnormal regions in different body organs has a crucial role in most of medical imaging applications such as funduscopy, endos…
Segmentation of Bleeding Regions in Wireless Capsule Endoscopy for Detection of Informative Frames
Mohsen Hajabdollahi, Reza Esfandiarpoor, Pejman Khadivi +4
Wireless capsule endoscopy (WCE) is an effective mean for diagnosis of gastrointestinal disorders. Detection of informative scenes in WCE video could reduce the length of transmitt…
Low complexity convolutional neural network for vessel segmentation in portable retinal diagnostic devices
M. Hajabdollahi, R. Esfandiarpoor, S. M. R. Soroushmehr +3
Retinal vessel information is helpful in retinal disease screening and diagnosis. Retinal vessel segmentation provides useful information about vessels and can be used by physician…
Segmentation of Bleeding Regions in Wireless Capsule Endoscopy Images an Approach for inside Capsule Video Summarization
Mohsen Hajabdollahi, Reza Esfandiarpoor, S. M. Reza Soroushmehr +3
Wireless capsule endoscopy (WCE) is an effective means of diagnosis of gastrointestinal disorders. Detection of informative scenes by WCE could reduce the length of transmitted vid…
Reversible Image Watermarking for Health Informatics Systems Using Distortion Compensation in Wavelet Domain
Hamidreza Zarrabi, Mohsen Hajabdollahi, S. M. Reza Soroushmehr +3
Reversible image watermarking guaranties restoration of both original cover and watermark logo from the watermarked image. Capacity and distortion of the image under reversible wat…
Lossless Compression of Angiogram Foreground with Visual Quality Preservation of Background
Mahdi Ahmadi, Ali Emami, Mohsen Hajabdollahi +4
By increasing the volume of telemedicine information, the need for medical image compression has become more important. In angiographic images, a small ratio of the entire image us…
Context aware saliency map generation using semantic segmentation
Mahdi Ahmadi, Mohsen Hajabdollahi, Nader Karimi +1
Saliency map detection, as a method for detecting important regions of an image, is used in many applications such as image classification and recognition. We propose that context…
Adaptive Real-Time Removal of Impulse Noise in Medical Images
Zohreh HosseinKhani, Mohsen Hajabdollahi, Nader Karimi +4
Noise is an important factor that degrades the quality of medical images. Impulse noise is a common noise, which is caused by malfunctioning of sensor elements or errors in the tra…
Real-Time Impulse Noise Removal from MR Images for Radiosurgery Applications
Zohreh HosseinKhani, Mohsen Hajabdollahi, Nader Karimi +4
In the recent years image processing techniques are used as a tool to improve detection and diagnostic capabilities in the medical applications. Medical applications have been so m…