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Apple (United Kingdom)

United Kingdom

13 papers here94 citations across 13
fields
  • cs.CL5
  • cs.CV2
  • cs.RO2
  • astro-ph.IM1
  • cs.GR1
  • cs.LG1
  • cs.SD1
ROR 01vpeym60OpenAlex

affiliations via OpenAlex

output
20182026
most citedThe Data Science of Hollywood: Using Emotional Arcs of Movies to Drive Business Model Innovation in Entertainment Industries

50 citations

researchers with a paper here
  • Aarshee Mishra1 · h 2
  • Abhijat Biswas1 · h 7
  • Adam Golinski1 · h 11
  • Ada V Taylor1 · h 4
  • Ahmed H. Tewfik1 · h 5
  • AI Sony1 · h 4
  • A. Kharlamov1 · h 6
  • Alexander Churchill1 · h 3
  • Alexander Toshev1 · h 42
  • Alexandre Alahi1 · h 45
  • Alexandre Bittar1 · h 4
  • A. Mousa1 · h 14
collaborating institutions
  • Adobe Systems (United States)US1 paper
  • Apple (United States)US1 paper
  • Aston UniversityGB1 paper
  • Bar-Ilan UniversityIL1 paper
  • Carnegie Mellon UniversityUS1 paper
  • Centre National de la Recherche ScientifiqueFR1 paper
  • École Polytechnique Fédérale de LausanneCH1 paper
  • Georgia Institute of TechnologyUS1 paper
  • Google (United States)US1 paper
  • Honda (Japan)JP1 paper
  • Italian Institute of TechnologyIT1 paper
  • Max Planck Institute for Intelligent SystemsDE1 paper
Showing 2020Show all

1 paper · 1 filter

cs.CV2020★ 9 cited

VAE-Info-cGAN: Generating Synthetic Images by Combining Pixel-level and Feature-level Geospatial Conditional Inputs

Xuerong Xiao, Swetava Ganguli, Vipul Pandey

Training robust supervised deep learning models for many geospatial applications of computer vision is difficult due to dearth of class-balanced and diverse training data. Converse…

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