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Recent Advances at the Brain-Driven Computer Vision Workshop 2018

  • Simone PalazzoEmail author
  • Isaak Kavasidis
  • Dimitris Kastaniotis
  • Stavros Dimitriadis
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11131)

Abstract

The 1\(^\text {st}\) edition of the Brain-Driven Computer Vision Workshop, held in Munich in conjunction with the European Conference on Computer Vision 2018, aimed at attracting, promoting and inspiring research on paradigms, methods and tools for computer vision driven or inspired by the human brain. While successful, in terms of the quality of received submissions and audience present at the event, the workshop emphasized some of the factors that currently limit research in this field. In this report, we discuss the success points of the workshop, the characteristics of the presented works, and our considerations on the state of current research and future directions of research in this topic.

Keywords

Brain-Driven Computer Vision Biologically-inspired machine learning 

List of Workshop Papers

  1. 1.
    Dwivedi, K., Roig, G.: Navigational affordance cortical responses explained by scene-parsing modelGoogle Scholar
  2. 2.
    Vascon, S., Parin, Y., Annavini, E., D’Andola, M., Zoccolan, D., Pelillo, M.: Characterization of visual object representations in rat primary visual cortexGoogle Scholar
  3. 3.
    Papadimitriou, A., Passalis, N., Tefas, A.: Decoding generic visual representations from human brain activity using machine learningGoogle Scholar
  4. 4.
    Jaiswal, A., AbdAlmageed, W., Wu, Y., Natarajan, P.: Capsulegan: Generative adversarial capsule networkGoogle Scholar
  5. 5.
    Ramasinghe, S., Athuraliya, C., Khan, S.: A context-aware capsule network for multi-label classificationGoogle Scholar
  6. 6.
    Strisciuglio, N., Azzopardi, G., Petkov, N.: Brain-inspired robust delineation operatorGoogle Scholar
  7. 7.
    Natsume, R., Inoue, K., Fukuhara, Y., Yamamoto, S., Morishima, S., Kataoka, H.: Understanding fake facesGoogle Scholar
  8. 8.
    Wever, R., Runia, T.F.: Subitizing with variational autoencodersGoogle Scholar
  9. 9.
    Dias, C., Dimiccoli, M.: Learning event representations by encoding the temporal contextGoogle Scholar
  10. 10.
    Nardo, E.D., Petrosino, A., Ullah, I.: Emop3d: A brain like pyramidal deep neural network for emotion recognitionGoogle Scholar

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Simone Palazzo
    • 1
    Email author
  • Isaak Kavasidis
    • 1
  • Dimitris Kastaniotis
    • 2
  • Stavros Dimitriadis
    • 3
  1. 1.University of CataniaCataniaItaly
  2. 2.University of PatrasPatrasGreece
  3. 3.Cardiff UniversityCardiffUK

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