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researcher

Georgios Evangelidis

University of Macedonia, Thessaloniki, Greece

4 papers hereh-index 192.3k citations129 works total

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

author position
  • middle author3
  • last author1

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

fields
  • cs.CV3
  • cs.LG1
affiliations
  • University of Macedonia, Thessaloniki, Greece
Homepage
same name
  • Georgios Evangelidis — 8 papers
  • Georgios Evangelidis — 1 paper
  • Georgios Evangelidis — 1 paper, h 2

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
20132023
most citedEfficientFormer: Vision Transformers at MobileNet Speed

257 citations · 278 across the 4 of their papers we have counts for

collaborators

4 papers

cs.CV2023

Continuous Cost Aggregation for Dual-Pixel Disparity Extraction

Sagi Monin, Sagi Katz, Georgios Evangelidis

Recent works have shown that depth information can be obtained from Dual-Pixel (DP) sensors. A DP arrangement provides two views in a single shot, thus resembling a stereo image pa…

cs.CV2022★ 21 cited

Rethinking Vision Transformers for MobileNet Size and Speed

Yanyu Li, Ju Hu, Yang Wen +5

With the success of Vision Transformers (ViTs) in computer vision tasks, recent arts try to optimize the performance and complexity of ViTs to enable efficient deployment on mobile…

cs.CV2022★ 257 cited

EfficientFormer: Vision Transformers at MobileNet Speed

Yanyu Li, Geng Yuan, Yang Wen +5

Vision Transformers (ViT) have shown rapid progress in computer vision tasks, achieving promising results on various benchmarks. However, due to the massive number of parameters an…

cs.LG2013

An Extensive Experimental Study on the Cluster-based Reference Set Reduction for speeding-up the k-NN Classifier

Stefanos Ougiaroglou, Georgios Evangelidis, Dimitris A. Dervos

The k-Nearest Neighbor (k-NN) classification algorithm is one of the most widely-used lazy classifiers because of its simplicity and ease of implementation. It is considered to be…

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