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researcher

S. Madden

46 papers hereh-index 9847.1k citations343 works total

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

author position
  • middle author28
  • last author16

Across the 44 of 46 papers where every author was matched, so the position is known.

fields
  • cs.DB29
  • cs.LG6
  • cs.CV4
  • cs.DC2
  • cs.PL2
  • cs.CL1
same name
  • S. Madden — 175 papers, h 67
  • S. Madden — 40 papers, h 22
  • S. Madden — 27 papers, h 4
  • S. Madden — 20 papers, h 11
  • S. Madden — 17 papers, h 51
  • S. Madden — 13 papers, h 7

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
20092023
most citedSprintz: Time Series Compression for the Internet of Things

130 citations · 606 across the 44 of their papers we have counts for

collaborators
Showing cs.CVShow all

4 papers · 1 filter

cs.CV2020★ 7 cited

Sat2Graph: Road Graph Extraction through Graph-Tensor Encoding

Songtao He, Favyen Bastani, Satvat Jagwani +6

Inferring road graphs from satellite imagery is a challenging computer vision task. Prior solutions fall into two categories: (1) pixel-wise segmentation-based approaches, which pr…

cs.CV2019★ 2 cited

RoadTagger: Robust Road Attribute Inference with Graph Neural Networks

Songtao He, Favyen Bastani, Satvat Jagwani +7

Inferring road attributes such as lane count and road type from satellite imagery is challenging. Often, due to the occlusion in satellite imagery and the spatial correlation of ro…

cs.CV2019★ 21 cited

Machine-Assisted Map Editing

Favyen Bastani, Songtao He, Sofiane Abbar +4

Mapping road networks today is labor-intensive. As a result, road maps have poor coverage outside urban centers in many countries. Systems to automatically infer road network graph…

cs.CV2018★ 26 cited

RoadTracer: Automatic Extraction of Road Networks from Aerial Images

Favyen Bastani, Songtao He, Sofiane Abbar +5

Mapping road networks is currently both expensive and labor-intensive. High-resolution aerial imagery provides a promising avenue to automatically infer a road network. Prior work…

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