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Behçet Uğur Töreyın

2 papers here

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

author position
  • last author2

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

fields
  • cs.CV1
  • cs.LG1
ORCID 0000-0003-4406-2783

identity via Semantic Scholar / OpenAlex

most citedFocus-and-Detect: A Small Object Detection Framework for Aerial Images

107 citations · 107 across the 2 of their papers we have counts for

collaborators

2 papers

cs.LG2024

Do deep neural networks utilize the weight space efficiently?

Onur Can Koyun, Behçet Uğur Töreyin

Deep learning models like Transformers and Convolutional Neural Networks (CNNs) have revolutionized various domains, but their parameter-intensive nature hampers deployment in reso…

cs.CV2022★ 107 cited

Focus-and-Detect: A Small Object Detection Framework for Aerial Images

Onur Can Koyun, Reyhan Kevser Keser, İbrahim Batuhan Akkaya +1

Despite recent advances, object detection in aerial images is still a challenging task. Specific problems in aerial images makes the detection problem harder, such as small objects…

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