Měření výpočetní síly podrobných spajkujících modelů biologického vidění.
| Thesis title in Czech: | Měření výpočetní síly podrobných spajkujících modelů biologického vidění. |
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| Thesis title in English: | Determination of the computational power of detailed spiking model of biological vision. |
| Academic year of topic announcement: | 2024/2025 |
| Thesis type: | diploma thesis |
| Thesis language: | |
| Department: | Department of Software and Computer Science Education (32-KSVI) |
| Supervisor: | Mgr. Ján Antolík, Ph.D. |
| Author: |
| Guidelines |
| Primary visual cortex is a complex recurrent dynamical system that operates quite differently from how moder neural network systems do. It however still remains unclear how does a biological V1 compare in its computational power to the state-of-the-art DNN systems for image analysis. In this project you will take our large-scale biologically dietailed spiking network model of cat primary visual cortex (V1) and prepend it to an existing state-of-the-art DNN system as its first stage of processing. You will then train both the original DNN and the new hybrid system on an image categorization benchmark and analyze the difference between the performance of the two systems. |
| References |
| 1. Daniel A. Butts. Data-Driven Approaches to Understanding Visual Neuron Activity (2019). Annual Reviews of Vision Neuroscience, 5:20.1–20.27
2. Cadena, S. A., Denfield, G. H., Walker, E. Y., Gatys, L. A., Tolias, A. S., Bethge, M., & Ecker, A. S. (2017). Deep convolutional models improve predictions of macaque V1 responses to natural images. bioRxiv, 201764. https://doi.org/10.1101/201764 3. Jan Antolık, Cyril Monier1, Yves Fregnac, and Andrew P. Davison (2019). A comprehensive data-driven model of cat primary visual cortex. BiorXiv 4. Konstantin-Klemens Lurz, Mohammad Bashiri, Konstantin Willeke, Akshay K. Jagadish, Eric Wang, Edgar Y. Walker, Santiago A. Cadena, Taliah Muhammad, Erick Cobos, Andreas S. Tolias, Alexander S. Ecker, Fabian H. Sinz (2020) Generalization in data-driven models of primary visual cortex. bioRxiv |