Computational modeling of human visual function using psychophysics, deep neural networks, and information theory

• Autores: Qiang Li
• Directores de la Tesis: Jesús Malo (dir. tes.)
• Lectura: En la Universitat de València ( España ) en 2023
• Idioma: inglés
• Tribunal Calificador de la Tesis: Shujian Yu (presid.), Valero Laparra Pérez-Muelas (secret.), Marina Martínez García (voc.)
• Enlaces
  • Tesis en acceso abierto en: webges.uv.es (pdf)
• Resumen

  • Visual perception is a key to unlocking the secrets of brain functions because most of the information is processed through the early visual system and then transmitted to the high-level cognitive perception brain regions. The brain functions as a self-organizing, bio-dynamic, and chaotic system that receives outside information and then decomposes it into pieces of information that can be processed efficiently and independently. The work connects natural image statistics, psychophysics, deep neural networks, and information theory to perceptual vision systems to explore how vision processes information from the outside world and how the information coupled drives functional connectivity between visual regions and even higher-level brain regions.