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Abdullah Al Mamun

4 papers hereh-index 282 citations12 works total

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

author position
  • first author1
  • middle author3

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

fields
  • cs.CV3
  • eess.IV1
same name
  • Abdullah Al Mamun — 18 papers, h 68
  • Abdullah Al Mamun — 4 papers, h 1
  • Abdullah Al Mamun — 2 papers, h 26
  • Abdullah Al Mamun — 2 papers
  • Abdullah Al Mamun — 1 paper
  • Abdullah Al Mamun — 1 paper, h 0

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

most citedStateSpace-SSL: Linear-Time Self-supervised Learning for Plant Disease Detection

1 citations · 1 across the 4 of their papers we have counts for

collaborators

4 papers

cs.CV2025★ 1 cited

StateSpace-SSL: Linear-Time Self-supervised Learning for Plant Disease Detection

Abdullah Al Mamun, Miaohua Zhang, David Ahmedt-Aristizabal +2

Self-supervised learning (SSL) is attractive for plant disease detection as it can exploit large collections of unlabeled leaf images, yet most existing SSL methods are built on CN…

cs.CV2025

EPSegFZ: Efficient Point Cloud Semantic Segmentation for Few- and Zero-Shot Scenarios with Language Guidance

Jiahui Wang, Haiyue Zhu, Haoren Guo +3

Recent approaches for few-shot 3D point cloud semantic segmentation typically require a two-stage learning process, i.e., a pre-training stage followed by a few-shot training stage…

cs.CV2025

SingRef6D: Monocular Novel Object Pose Estimation with a Single RGB Reference

Jiahui Wang, Haiyue Zhu, Haoren Guo +3

Recent 6D pose estimation methods demonstrate notable performance but still face some practical limitations. For instance, many of them rely heavily on sensor depth, which may fail…

eess.IV2022

CAM/CAD Point Cloud Part Segmentation via Few-Shot Learning

Jiahui Wang, Haiyue Zhu, Haoren Guo +3

3D part segmentation is an essential step in advanced CAM/CAD workflow. Precise 3D segmentation contributes to lower defective rate of work-pieces produced by the manufacturing equ…

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