43 citations · 98 across the 19 of their papers we have counts for
21 papers
The Deep Arbitrary Polynomial Chaos Neural Network or how Deep Artificial Neural Networks could benefit from Data-Driven Homogeneous Chaos Theory
Sergey Oladyshkin, Timothy Praditia, Ilja Kröker +3
Artificial Intelligence and Machine learning have been widely used in various fields of mathematical computing, physical modeling, computational science, communication science, and…
Deep Learning in Healthcare: An In-Depth Analysis
Farzan Shenavarmasouleh, Farid Ghareh Mohammadi, Khaled M. Rasheed +1
Deep learning (DL) along with never-ending advancements in computational processing and cloud technologies have bestowed us powerful analyzing tools and techniques in the past deca…
3D-model ShapeNet Core Classification using Meta-Semantic Learning
Farid Ghareh Mohammadi, Cheng Chen, Farzan Shenavarmasouleh +3
Understanding 3D point cloud models for learning purposes has become an imperative challenge for real-world identification such as autonomous driving systems. A wide variety of sol…
The application of Evolutionary and Nature Inspired Algorithms in Data Science and Data Analytics
Farid Ghareh Mohammadi, Farzan Shenavarmasouleh, Khaled Rasheed +3
In the past 30 years, scientists have searched nature, including animals and insects, and biology in order to discover, understand, and model solutions for solving large-scale scie…
Applications of Machine Learning in Healthcare and Internet of Things (IOT): A Comprehensive Review
Farid Ghareh Mohammadi, Farzan Shenavarmasouleh, Hamid R. Arabnia
In recent years, smart healthcare IoT devices have become ubiquitous, but they work in isolated networks due to their policy. Having these devices connected in a network enables us…
OptABC: an Optimal Hyperparameter Tuning Approach for Machine Learning Algorithms
Leila Zahedi, Farid Ghareh Mohammadi, M. Hadi Amini
Hyperparameter tuning in machine learning algorithms is a computationally challenging task due to the large-scale nature of the problem. In order to develop an efficient strategy f…
Data Analytics for Smart cities: Challenges and Promises
Farid Ghareh Mohammadi, Farzan Shenavarmasouleh, M. Hadi Amini +1
The explosion of advancements in artificial intelligence, sensor technologies, and wireless communication activates ubiquitous sensing through distributed sensors. These sensors ar…
HyP-ABC: A Novel Automated Hyper-Parameter Tuning Algorithm Using Evolutionary Optimization
Leila Zahedi, Farid Ghareh Mohammadi, M. Hadi Amini
Machine learning techniques lend themselves as promising decision-making and analytic tools in a wide range of applications. Different ML algorithms have various hyper-parameters.…
Embodied AI-Driven Operation of Smart Cities: A Concise Review
Farzan Shenavarmasouleh, Farid Ghareh Mohammadi, M. Hadi Amini +1
A smart city can be seen as a framework, comprised of Information and Communication Technologies (ICT). An intelligent network of connected devices that collect data with their sen…
DRDrV3: Complete Lesion Detection in Fundus Images Using Mask R-CNN, Transfer Learning, and LSTM
Farzan Shenavarmasouleh, Farid Ghareh Mohammadi, M. Hadi Amini +3
Medical Imaging is one of the growing fields in the world of computer vision. In this study, we aim to address the Diabetic Retinopathy (DR) problem as one of the open challenges i…
Search Algorithms for Automated Hyper-Parameter Tuning
Leila Zahedi, Farid Ghareh Mohammadi, Shabnam Rezapour +2
Machine learning is a powerful method for modeling in different fields such as education. Its capability to accurately predict students' success makes it an ideal tool for decision…
Malware Detection using Artificial Bee Colony Algorithm
Farid Ghareh Mohammadi, Farzan Shenavarmasouleh, M. Hadi Amini +1
Malware detection has become a challenging task due to the increase in the number of malware families. Universal malware detection algorithms that can detect all the malware famili…
DRDr II: Detecting the Severity Level of Diabetic Retinopathy Using Mask RCNN and Transfer Learning
Farzan Shenavarmasouleh, Farid Ghareh Mohammadi, M. Hadi Amini +1
DRDr II is a hybrid of machine learning and deep learning worlds. It builds on the successes of its antecedent, namely, DRDr, that was trained to detect, locate, and create segment…
Surrogate-based Bayesian Comparison of Computationally Expensive Models: Application to Microbially Induced Calcite Precipitation
Stefania Scheurer, Aline Schäfer Rodrigues Silva, Farid Mohammadi +4
Geochemical processes in subsurface reservoirs affected by microbial activity change the material properties of porous media. This is a complex biogeochemical process in subsurface…
Development and Realization of Validation Benchmarks
Farid Mohammadi
In the field of modeling, the word validation refers to simple comparisons between model outputs and experimental data. Usually, this comparison constitutes plotting the model resu…
DeepMSRF: A novel Deep Multimodal Speaker Recognition framework with Feature selection
Ehsan Asali, Farzan Shenavarmasouleh, Farid Ghareh Mohammadi +2
For recognizing speakers in video streams, significant research studies have been made to obtain a rich machine learning model by extracting high-level speaker's features such as f…
On Parameter Tuning in Meta-learning for Computer Vision
Farid Ghareh Mohammadi, M. Hadi Amini, Hamid R. Arabnia
Learning to learn plays a pivotal role in meta-learning (MTL) to obtain an optimal learning model. In this paper, we investigate mage recognition for unseen categories of a given d…
An Introduction to Advanced Machine Learning : Meta Learning Algorithms, Applications and Promises
Farid Ghareh Mohammadi, M. Hadi Amini, Hamid R. Arabnia
In [1, 2], we have explored the theoretical aspects of feature extraction optimization processes for solving largescale problems and overcoming machine learning limitations. Majori…
Applications of Nature-Inspired Algorithms for Dimension Reduction: Enabling Efficient Data Analytics
Farid Ghareh Mohammadi, M. Hadi Amini, Hamid R. Arabnia
In [1], we have explored the theoretical aspects of feature selection and evolutionary algorithms. In this chapter, we focus on optimization algorithms for enhancing data analytic…
Evolutionary Computation, Optimization and Learning Algorithms for Data Science
Farid Ghareh Mohammadi, M. Hadi Amini, Hamid R. Arabnia
A large number of engineering, science and computational problems have yet to be solved in a computationally efficient way. One of the emerging challenges is how evolving technolog…
Evolutionary Algorithms and Efficient Data Analytics for Image Processing
Farid Ghareh Mohammadi, Farzan Shenavarmasouleh, M. Hadi Amini +1
Steganography algorithms facilitate communication between a source and a destination in a secret manner. This is done by embedding messages/text/data into images without impacting…