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researcher

Moloud Abdar

3 papers here

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

author position
  • middle author2

Across the 2 of 3 papers where every author was matched, so the position is known.

fields
  • cs.LG2
  • cs.CV1
ORCID 0000-0002-3059-6357

identity via Semantic Scholar / OpenAlex

most citedA Review of Deep Learning for Video Captioning

9 citations · 9 across the 3 of their papers we have counts for

collaborators

3 papers

cs.CV2023★ 9 cited

A Review of Deep Learning for Video Captioning

Moloud Abdar, Meenakshi Kollati, Swaraja Kuraparthi +8

Video captioning (VC) is a fast-moving, cross-disciplinary area of research that bridges work in the fields of computer vision, natural language processing (NLP), linguistics, and…

cs.LG2023

Survey on Leveraging Uncertainty Estimation Towards Trustworthy Deep Neural Networks: The Case of Reject Option and Post-training Processing

Mehedi Hasan, Moloud Abdar, Abbas Khosravi +5

Although neural networks (especially deep neural networks) have achieved \textit{better-than-human} performance in many fields, their real-world deployment is still questionable du…

cs.LG2023

SFE: A Simple, Fast and Efficient Feature Selection Algorithm for High-Dimensional Data

Behrouz Ahadzadeh, Moloud Abdar, Fatemeh Safara +3

In this paper, a new feature selection algorithm, called SFE (Simple, Fast, and Efficient), is proposed for high-dimensional datasets. The SFE algorithm performs its search process…

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