no code implementations • 17 Jan 2024 • Elaheh Motamedi, Kian Behzad, Rojin Zandi, Hojjat Salehinejad, Milad Siami
This paper studies robot arm action recognition in noisy environments using machine learning techniques.
1 code implementation • 31 Jul 2023 • Navid Hasanzadeh, Shahrokh Valaee, Hojjat Salehinejad
Although some studies suggest a relationship between blood pressure and certain vital signals, such as Photoplethysmogram (PPG), reliable generalization of the proposed blood pressure estimation methods is not yet guaranteed.
Ranked #1 on Hypertension detection on MIMIC-III
1 code implementation • 7 Mar 2022 • Hojjat Salehinejad, Yang Wang, Yuanhao Yu, Tang Jin, Shahrokh Valaee
A population-based optimization algorithm evolves the population in order to find a best state vector which minimizes the number of active kernels while maximizing the accuracy of the classifier.
no code implementations • 25 Feb 2021 • Hojjat Salehinejad, Shahrokh Valaee
A typical deep neural network (DNN) has a large number of trainable parameters.
1 code implementation • 10 Feb 2021 • Hojjat Salehinejad, Shahrokh Valaee
Pruning is one of the major methods to compress deep neural networks.
no code implementations • 9 Feb 2021 • Hojjat Salehinejad, Jumpei Kitamura, Noah Ditkofsky, Amy Lin, Aditya Bharatha, Suradech Suthiphosuwan, Hui-Ming Lin, Jefferson R. Wilson, Muhammad Mamdani, Errol Colak
An ML model was trained using 21, 784 scans from the RSNA Intracranial Hemorrhage CT dataset while generalizability was evaluated using an external validation dataset obtained from our busy trauma and neurosurgical center.
no code implementations • 26 Oct 2020 • Hojjat Salehinejad, Edward Ho, Hui-Ming Lin, Priscila Crivellaro, Oleksandra Samorodova, Monica Tafur Arciniegas, Zamir Merali, Suradech Suthiphosuwan, Aditya Bharatha, Kristen Yeom, Muhammad Mamdani, Jefferson Wilson, Errol Colak
Fractures of the cervical spine are a medical emergency and may lead to permanent paralysis and even death.
2 code implementations • 7 Jun 2020 • Hojjat Salehinejad, Shahrokh Valaee
The energy-based model stochastically evolves the population to find states with lower energy loss.
no code implementations • 25 Apr 2019 • Alex Labach, Hojjat Salehinejad, Shahrokh Valaee
Dropout methods are a family of stochastic techniques used in neural network training or inference that have generated significant research interest and are widely used in practice.
no code implementations • 7 Feb 2019 • Hojjat Salehinejad, Shahrokh Valaee
In this paper, we propose an adaptive technique to wisely drop the visible and hidden units in a deep neural network using Ising energy of the network.
no code implementations • 24 Sep 2018 • Hojjat Salehinejad, Sumeya Naqvi, Errol Colak, Joseph Barfett, Shahrokh Valaee
The images generated from a cylindrical transform augment a limited annotated set of images in three dimensions.
no code implementations • 29 Dec 2017 • Hojjat Salehinejad, Sharan Sankar, Joseph Barfett, Errol Colak, Shahrokh Valaee
Recurrent neural networks (RNNs) are capable of learning features and long term dependencies from sequential and time-series data.
no code implementations • 8 Nov 2017 • Hojjat Salehinejad, Shahrokh Valaee, Tim Dowdell, Errol Colak, Joseph Barfett
Medical datasets are often highly imbalanced with over-representation of common medical problems and a paucity of data from rare conditions.
no code implementations • 8 Sep 2017 • Hojjat Salehinejad, Shahryar Rahnamayan, Hamid. R. Tizhoosh
Differential evolution (DE) algorithm with a small population size is called Micro-DE (MDE).
no code implementations • 24 Aug 2017 • Hojjat Salehinejad, Shahrokh Valaee, Aren Mnatzakanian, Tim Dowdell, Joseph Barfett, Errol Colak
Radiology reports are an important means of communication between radiologists and other physicians.
no code implementations • 14 Aug 2017 • Hojjat Salehinejad, Shahrokh Valaee, Timothy Dowdell, Joseph Barfett
We propose a sampling method based on the radial transform in a polar coordinate system for image augmentation to facilitate the training of deep learning models from limited source data.
no code implementations • 7 Aug 2017 • Hojjat Salehinejad, Joseph Barfett, Parham Aarabi, Shahrokh Valaee, Errol Colak, Bruce Gray, Tim Dowdell
Pathfinding in hospitals is challenging for patients, visitors, and even employees.
no code implementations • 13 Feb 2016 • Hojjat Salehinejad
This paper provides a fundamental review on RNNs and long short term memory (LSTM) model.
no code implementations • 25 Dec 2015 • Hojjat Salehinejad, Shahryar Rahnamayan, Hamid. R. Tizhoosh
Furthermore, comprehensive comparative simulations and analysis on performance of the MDE algorithms over various mutation schemes, population sizes, problem types (i. e. uni-modal, multi-modal, and composite), problem dimensionalities, and mutation factor ranges are conducted by considering population diversity analysis for stagnation and trapping in local optimum situations.
no code implementations • 9 Nov 2015 • Farhad Pouladi, Hojjat Salehinejad, Amir Mohammad Gilani
In analyzing of modern biological data, we are often dealing with ill-posed problems and missing data, mostly due to high dimensionality and multicollinearity of the dataset.
no code implementations • 28 Apr 2015 • Hojjat Salehinejad, Hossein Nezamabadi-pour, Saeid Saryazdi, Fereydoun Farrahi-Moghaddam
In this paper a multi-parameter A*(A- star)-ants based algorithm is proposed in order to find the best optimized multi-parameter path between two desired points in regions.
no code implementations • 28 Apr 2015 • Hojjat Salehinejad, Farhad Pouladi, Siamak Talebi
In smart power grids, keeping the synchronicity of generators and the corresponding controls is of great importance.