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researcher

Mahamudul Hasan

Research Assistant, Department of Computer Science and Engineering, University of Minnesota, Twin Cities

4 papers hereh-index 11497 citations60 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • sole author2
  • first author1
  • last author1

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.IR3
  • cs.CV1
affiliations
  • Research Assistant, Department of Computer Science and Engineering, University of Minnesota, Twin Cities
  • Senior Lecturer (On Study Leave), East West University
ORCID 0000-0002-4311-8688
same name
  • Mahamudul Hasan — 1 paper, h 0
  • Mahamudul Hasan — 1 paper, h 0
  • Mahamudul Hasan — 1 paper, h 2
  • Mahamudul Hasan — 1 paper, h 0
  • Mahamudul Hasan — 1 paper, h 4

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

collaborators

4 papers

cs.IR2024

ECORS: An Ensembled Clustering Approach to Eradicate The Local And Global Outlier In Collaborative Filtering Recommender System

Mahamudul Hasan

Recommender systems are designed to suggest items based on user preferences, helping users navigate the vast amount of information available on the internet. Given the overwhelming…

cs.IR2024

Utilizing Collaborative Filtering in a Personalized Research-Paper Recommendation System

Mahamudul Hasan, Anika Tasnim Islam, Nabila Islam

Recommendation system is such a platform that helps people to easily find out the things they need within a few seconds. It is implemented based on the preferences of similar users…

cs.IR2024

An Efficient Multi-threaded Collaborative Filtering Approach in Recommendation System

Mahamudul Hasan

Recommender systems are a subset of information filtering systems designed to predict and suggest items that users may find interesting or relevant based on their preferences, beha…

cs.CV2024

Advancing Cucumber Disease Detection in Agriculture through Machine Vision and Drone Technology

Syada Tasfia Rahman, Nishat Vasker, Amir Khabbab Ahammed +1

This study uses machine vision and drone technologies to propose a unique method for the diagnosis of cucumber disease in agriculture. The backbone of this research is a painstakin…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.