Mohsen Ramezani

Education

PhD. in Computer engineering-Artificial Intelligence , Semnan university , Iran (2013 - 2018)
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MSc. in Computer engineering-Artificial Intelligence , University of Kurdistan , Iran (2011 - 2013)
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BSc. in Information Technology engineering , University of Kurdistan , Iran (2007 - 2011)
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Courses

Bachelor Of Science

Concepts of computer systems

Data Mining

Artificial Intelligence

Software design

Fundamentals of programming in c++

Computer graphics

Data structures and algorithms

Concepts of Operating Systems

Advanced Programming

Master Of Science

Machine Vision

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Research activities

Journal Papers

Automated grading of oleaster fruit using deep learning Aram Azadpour, Kaveh Mollazade, Mohsen Ramezani, Hadi Samimi Akhijahani (2025)

A New Deep Vision-Based Identifier As An Intelligent Herbicide Spraying Agent For Potato Farm Application (1403)

Robust deep image-watermarking method by a modified Siamese network Ako Bartani, Fardin Akhlaghian Tab, Alireza Abdollahpouri, Mohsen Ramezani (2024)

An adaptive optic-physic based dust removal method using optimized air-light and transfer function Ako Bartani, Alireza Abdollahpouri, Mohsen Ramezani, Fardin Akhlaghian Tab (2022)

A Deep Human Action Representation For Retrieval Application Mohsen Ramezani, Fardin Akhlaghian Tab, Farzin Yaghmaee (2022)

A novel extreme learning machine based kNN classification method for dealing with big data Amin Shokrzade, Mohsen Ramezani, Fardin Akhlaghian Tab, Mahmud Abdulla Mohammad (2021)

A new generalized collaborative filtering approach on sparse data by extracting high confidence relations between users Mohsen Ramezani, Fardin Akhlaghian Tab, Alireza Abdollahpouri, Mahmud Abdulla Mohammad (2021)

ELM-NET, a closer to practice approach for classifying the big data using multiple independent ELMs Amin Shokrzade, Fardin Akhlaghian Tab, Mohsen Ramezani (2020)

Motion pattern based representation for improving human action retrieval Mohsen Ramezani, Farzin Yaghmaee (2018)

Retrieving Human Action by Fusing the Motion Information of Interest Points Mohsen Ramezani, Farzin Yaghmaee (2018)

A review on human action analysis in videos for retrieval applications Mohsen Ramezani, Farzin Yaghmaee (2016)

A novel video recommendation system based on efficient retrieval of human actions Mohsen Ramezani, Farzin Yaghmaee (2016)

A pattern mining approach to enhancing the accuracy of collaborative filtering in sparse data domains Mohsen Ramezani, Parham Moradi, Fardin Akhlaghian Tab (2014)

Conference Papers

Eliminating the Repetitive Motions as a Preprocessing step for Fast Human Action Retrieval Mohsen Ramezani, Farzin Yaghmaee (2019)

Content-based human actions retrieval by a novel low complex action representation Mohsen Ramezani, Farzin Yaghmaee (2014)

Using the Fuzzy Clustering Algorithm to Improve the Content-Based Action Retrieval Mohsen Ramezani, Farzin Yaghmaee (2014)

Content-based retrieval of human actions by analysing the statistical information of features Mohsen Ramezani, Farzin Yaghmaee (2014)

Improve performance of collaborative filtering systems using backward feature selection Mohsen Ramezani, Parham Moradi, Fardin Akhlaghian Tab (2013)

A New Hybrid Clustering Algorithm for Improving Results of Recommender Systems Mohsen Ramezani, Parham Moradi (2013)

Theses

Design and implementation of a high-speed online system based on deep learning for grading of oleaster (Elaeagnus angustifolia) fruit (1402)

A Filter-Wrapper Many-Objective Multi-label Feature Selection (1402)

The effect of content marketing on audience attraction in Instagram social network (1401)

presenting a two-stream method based on traditional and deep complementary features to detect human activity in video (1401)

GAN-Based Guided Image Inpainting By User-defined Side Information Mohsen Ramezani, Fardin Akhlaghian Tab (2022)

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Research interests

Information retrieval in videos
Big data
Analyzing the human actions in videos
Collaborative filtering systems

Academic Website

Mohsen Ramezani

Education

Courses

Research activities

Research interests

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