Search Results for author: Hamid R. Arabnia

Found 26 papers, 2 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

EXPANSE: A Deep Continual / Progressive Learning System for Deep Transfer Learning

1 code implementation19 May 2022 Mohammadreza Iman, John A. Miller, Khaled Rasheed, Robert M. Branch, Hamid R. Arabnia

Deep transfer learning techniques try to tackle the limitations of deep learning, the dependency on extensive training data and the training costs, by reusing obtained knowledge.

Continual Learning Transfer Learning

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.

Generative Adversarial Network Applications in Creating a Meta-Universe

no code implementations23 Jan 2022 Soheyla Amirian, Thiab R. Taha, Khaled Rasheed, Hamid R. Arabnia

Generative Adversarial Networks (GANs) are machine learning methods that are used in many important and novel applications.

Image-to-Image Translation Translation +2

A Review of Deep Transfer Learning and Recent Advancements

no code implementations19 Jan 2022 Mohammadreza Iman, Khaled Rasheed, Hamid R. Arabnia

A successful deep learning model is dependent on extensive training data and processing power and time (known as training costs).

Transfer 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

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

Sarcasm Detection: A Comparative Study

no code implementations5 Jul 2021 Hamed Yaghoobian, Hamid R. Arabnia, Khaled Rasheed

Sarcasm detection is the task of identifying irony containing utterances in sentiment-bearing text.

Sarcasm Detection Sentiment Analysis

Automatic Generation of Descriptive Titles for Video Clips Using Deep Learning

no code implementations7 Apr 2021 Soheyla Amirian, Khaled Rasheed, Thiab R. Taha, Hamid R. Arabnia

The proposed system functions and operates as followed: it reads a video; representative image frames are identified and selected; the image frames are captioned; NLP is applied to all generated captions together with text summarization; and finally, a title and an abstract are generated for the video.

Text Summarization Video Captioning

The Use of Video Captioning for Fostering Physical Activity

no code implementations7 Apr 2021 Soheyla Amirian, Abolfazl Farahani, Hamid R. Arabnia, Khaled Rasheed, Thiab R. Taha

With the above in mind, this paper proposes a video captioning framework that aims to describe the activities in a video and estimate a person's daily physical activity level.

Action Detection object-detection +2

A Concise Review of Transfer Learning

no code implementations5 Apr 2021 Abolfazl Farahani, Behrouz Pourshojae, Khaled Rasheed, Hamid R. Arabnia

The availability of abundant labeled data in recent years led the researchers to introduce a methodology called transfer learning, which utilizes existing data in situations where there are difficulties in collecting new annotated data.

Transfer Learning

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

A Brief Review of Domain Adaptation

no code implementations7 Oct 2020 Abolfazl Farahani, Sahar Voghoei, Khaled Rasheed, Hamid R. Arabnia

However, This assumption may not always hold in real-world applications where the training and the test data fall from different distributions, due to many factors, e. g., collecting the training and test sets from different sources, or having an out-dated training set due to the change of data over time.

BIG-bench Machine Learning Unsupervised Domain Adaptation

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

DRDr: Automatic Masking of Exudates and Microaneurysms Caused By Diabetic Retinopathy Using Mask R-CNN and Transfer Learning

no code implementations4 Jul 2020 Farzan Shenavarmasouleh, Hamid R. Arabnia

This paper addresses the problem of identifying two main types of lesions - Exudates and Microaneurysms - caused by Diabetic Retinopathy (DR) in the eyes of diabetic patients.

Data Augmentation Transfer Learning

Deep Learning at the Edge

no code implementations22 Oct 2019 Sahar Voghoei, Navid Hashemi Tonekaboni, Jason G. Wallace, Hamid R. Arabnia

The ever-increasing number of Internet of Things (IoT) devices has created a new computing paradigm, called edge computing, where most of the computations are performed at the edge devices, rather than on centralized servers.

Edge-computing

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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