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Muhammad Usman

6 papers hereh-index 51.7k citations9 works total

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

author position
  • middle author5
  • last author1

Across the 6 of 6 papers where every author was matched, so the position is known.

fields
  • cs.CV3
  • cs.CL2
  • eess.IV1
same name
  • Muhammad Usman — 15 papers, h 5
  • Muhammad Usman — 11 papers, h 12
  • Muhammad Usman — 10 papers, h 17
  • Muhammad Usman — 10 papers, h 3
  • Muhammad Usman — 9 papers, h 10
  • Muhammad Usman — 8 papers, h 7

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

activity
20232026
most citedA Comprehensive Overview of Large Language Models

369 citations · 393 across the 6 of their papers we have counts for

collaborators
Showing 2024Show all

4 papers · 1 filter

eess.IV2024

Attention Down-Sampling Transformer, Relative Ranking and Self-Consistency for Blind Image Quality Assessment

Mohammed Alsaafin, Musab Alsheikh, Saeed Anwar +1

The no-reference image quality assessment is a challenging domain that addresses estimating image quality without the original reference. We introduce an improved mechanism to extr…

cs.CL2024★ 2 cited

DefAn: Definitive Answer Dataset for LLMs Hallucination Evaluation

A B M Ashikur Rahman, Saeed Anwar, Muhammad Usman +1

Large Language Models (LLMs) have demonstrated remarkable capabilities, revolutionizing the integration of AI in daily life applications. However, they are prone to hallucinations,…

cs.CV2024★ 1 cited

Bird Eye-View to Street-View: A Survey

Khawlah Bajbaa, Muhammad Usman, Saeed Anwar +2

In recent years, street view imagery has grown to become one of the most important sources of geospatial data collection and urban analytics, which facilitates generating meaningfu…

cs.CV2024★ 21 cited

Deep Models for Multi-View 3D Object Recognition: A Review

Mona Alzahrani, Muhammad Usman, Salma Kammoun +2

Human decision-making often relies on visual information from multiple perspectives or views. In contrast, machine learning-based object recognition utilizes information from a sin…

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