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Samuel Felipe dos Santos

4 papers hereh-index 27 citations4 works total

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

author position
  • first author3
  • middle author1

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

fields
  • cs.CV4
same name
  • Samuel Felipe dos Santos — 4 papers, h 6
  • Samuel Felipe dos Santos — 2 papers
  • Samuel Felipe dos Santos — 1 paper
  • Samuel Felipe dos Santos — 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
20202026
most citedCNNs for JPEGs: A Study in Computational Cost

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

collaborators

4 papers

cs.CV2026

Efficient Spatio-Temporal Vegetation Pixel Classification with Vision Transformers

Alan Gomes, Anderson Gonçalves, Samuel Felipe dos Santos +6

Plant phenology-the study of recurrent life cycle events-is essential for understanding ecosystem dynamics and their responses to climate change impacts. While Unmanned Aerial Vehi…

cs.CV2023★ 2 cited

CNNs for JPEGs: A Study in Computational Cost

Samuel Felipe dos Santos, Nicu Sebe, Jurandy Almeida

Convolutional neural networks (CNNs) have achieved astonishing advances over the past decade, defining state-of-the-art in several computer vision tasks. CNNs are capable of learni…

cs.CV2021★ 2 cited

Less is More: Accelerating Faster Neural Networks Straight from JPEG

Samuel Felipe dos Santos, Jurandy Almeida

Most image data available are often stored in a compressed format, from which JPEG is the most widespread. To feed this data on a convolutional neural network (CNN), a preliminary…

cs.CV2020

CNNs for JPEGs: A Study in Computational Cost

Samuel Felipe dos Santos, Nicu Sebe, Jurandy Almeida

Convolutional neural networks (CNNs) have achieved astonishing advances over the past decade, defining state-of-the-art in several computer vision tasks. CNNs are capable of learni…

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