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Tom Gedeon

ANU, Murdoch University, UNSW, Brunel University, Flinders University, UWA, Curtin University

35 papers hereh-index 439.8k citations502 works total

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

author position
  • middle author13
  • last author19

Across the 32 of 35 papers where every author was matched, so the position is known.

fields
  • cs.CV20
  • cs.HC5
  • cs.NE4
  • cs.LG2
  • cs.CL1
  • cs.CR1
affiliations
  • ANU, Murdoch University, UNSW, Brunel University, Flinders University, UWA, Curtin University
same name
  • Tom Gedeon — 11 papers, h 9
  • Tom Gedeon — 9 papers, h 6
  • Tom Gedeon — 2 papers, h 3
  • Tom Gedeon — 1 paper
  • Tom Gedeon — 1 paper
  • Tom Gedeon — 1 paper

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
20162023
most citedRisk and Ambiguity in Information Seeking: Eye Gaze Patterns Reveal Contextual Behaviour in Dealing with Uncertainty

40 citations · 177 across the 35 of their papers we have counts for

collaborators
Showing 2022Show all

3 papers · 1 filter

cs.CV2022★ 37 cited

Deep transfer learning for image classification: a survey

Jo Plested, Musa Phiri, Tom Gedeon

Deep neural networks such as convolutional neural networks (CNNs) and transformers have achieved many successes in image classification in recent years. It has been consistently de…

cs.CV2022★ 1 cited

Representation-Centric Survey of Supervised Skeletal Action Recognition and the New Benchmark

Yang Liu, Jiyao Yang, Madhawa Perera +8

3D skeletal action recognition has emerged as a powerful alternative to traditional RGB and depth-based approaches, offering robustness to environmental variations, computational e…

cs.CV2022

Attribute Descent: Simulating Object-Centric Datasets on the Content Level and Beyond

Yue Yao, Liang Zheng, Xiaodong Yang +2

This article aims to use graphic engines to simulate a large number of training data that have free annotations and possibly strongly resemble to real-world data. Between synthetic…

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