Search Results for author: Farid Ghareh Mohammadi

Found 17 papers, 1 papers with code

3D-model ShapeNet Core Classification using Meta-Semantic Learning

no code implementations28 May 2022 Farid Ghareh Mohammadi, Cheng Chen, Farzan Shenavarmasouleh, M. Hadi Amini, Beshoy Morkos, Hamid R. Arabnia

Understanding 3D point cloud models for learning purposes has become an imperative challenge for real-world identification such as autonomous driving systems.

Autonomous Driving Classification +4

The application of Evolutionary and Nature Inspired Algorithms in Data Science and Data Analytics

no code implementations6 Feb 2022 Farid Ghareh Mohammadi, Farzan Shenavarmasouleh, Khaled Rasheed, Thiab Taha, M. Hadi Amini, Hamid R. Arabnia

In this study, we present our discovery of evolutionary and nature-inspired algorithms applications in Data Science and Data Analytics in three main topics of pre-processing, supervised algorithms, and unsupervised algorithms.

Applications of Machine Learning in Healthcare and Internet of Things (IOT): A Comprehensive Review

no code implementations6 Feb 2022 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.

OptABC: an Optimal Hyperparameter Tuning Approach for Machine Learning Algorithms

no code implementations15 Dec 2021 Leila Zahedi, Farid Ghareh Mohammadi, M. Hadi Amini

OptABC integrates artificial bee colony algorithm, K-Means clustering, greedy algorithm, and opposition-based learning strategy for tuning the hyper-parameters of different machine learning models.

BIG-bench Machine Learning

Data Analytics for Smart cities: Challenges and Promises

no code implementations12 Sep 2021 Farid Ghareh Mohammadi, Farzan Shenavarmasouleh, M. Hadi Amini, Hamid R. Arabnia

Then, we offer a framework of these solutions, called universal smart cities decision making, with three main sections of data capturing, data analysis, and decision making to optimize the smart mobility within smart cities.

Decision Making

HyP-ABC: A Novel Automated Hyper-Parameter Tuning Algorithm Using Evolutionary Optimization

no code implementations11 Sep 2021 Leila Zahedi, Farid Ghareh Mohammadi, M. Hadi Amini

In order to ensure the robustness of the proposed method, the algorithm takes a wide range of feasible hyper-parameter values, and is tested using a real-world educational dataset.

Decision Making

Embodied AI-Driven Operation of Smart Cities: A Concise Review

no code implementations22 Aug 2021 Farzan Shenavarmasouleh, Farid Ghareh Mohammadi, M. Hadi Amini, Hamid R. Arabnia

Embodied AI aims to train an agent that can See (Computer Vision), Talk (NLP), Navigate and Interact with its environment (Reinforcement Learning), and Reason (General Intelligence), all at the same time.

Autonomous Driving Navigate

Search Algorithms for Automated Hyper-Parameter Tuning

1 code implementation29 Apr 2021 Leila Zahedi, Farid Ghareh Mohammadi, Shabnam Rezapour, Matthew W. Ohland, M. Hadi Amini

In this paper, we examine the effectiveness of automated hyper-parameter tuning techniques to the realm of students' success.

BIG-bench Machine Learning Decision Making

Malware Detection using Artificial Bee Colony Algorithm

no code implementations1 Dec 2020 Farid Ghareh Mohammadi, Farzan Shenavarmasouleh, M. Hadi Amini, Hamid R. Arabnia

However, the more universal an algorithm is, the higher number of feature dimensions it needs to work with, and that inevitably causes the emerging problem of Curse of Dimensionality (CoD).

Malware Analysis Malware Detection

DeepMSRF: A novel Deep Multimodal Speaker Recognition framework with Feature selection

no code implementations14 Jul 2020 Ehsan Asali, Farzan Shenavarmasouleh, Farid Ghareh Mohammadi, Prasanth Sengadu Suresh, Hamid R. Arabnia

The goal of DeepMSRF is to identify the gender of the speaker first, and further to recognize his or her name for any given video stream.

Speaker Recognition

An Introduction to Advanced Machine Learning : Meta Learning Algorithms, Applications and Promises

no code implementations26 Aug 2019 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.

BIG-bench Machine Learning Meta-Learning

Applications of Nature-Inspired Algorithms for Dimension Reduction: Enabling Efficient Data Analytics

no code implementations22 Aug 2019 Farid Ghareh Mohammadi, M. Hadi Amini, Hamid R. Arabnia

Dimension reduction, together with EAs, lends itself to solve CoD and solve complex problems, in terms of time complexity, efficiently.

Credit score Dimensionality Reduction +1

Evolutionary Computation, Optimization and Learning Algorithms for Data Science

no code implementations16 Aug 2019 Farid Ghareh Mohammadi, M. Hadi Amini, Hamid R. Arabnia

We focus on data science as a crucial area, specifically focusing on a curse of dimensionality (CoD) which is due to the large amount of generated/sensed/collected data.

Decision Making

Evolutionary Algorithms and Efficient Data Analytics for Image Processing

no code implementations23 Jul 2019 Farid Ghareh Mohammadi, Farzan Shenavarmasouleh, M. Hadi Amini, Hamid R. Arabnia

However, the increase in features leads to the problem of the curse of dimensionality (CoD), which is considered to be an NP-hard problem.

BIG-bench Machine Learning

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