whereismymnist
localization in computer vision = colliculus to predict accuracy + active vision through saccades
Science Score: 26.0%
This score indicates how likely this project is to be science-related based on various indicators:
-
○CITATION.cff file
-
✓codemeta.json file
Found codemeta.json file -
✓.zenodo.json file
Found .zenodo.json file -
○DOI references
-
○Academic publication links
-
○Academic email domains
-
○Institutional organization owner
-
○JOSS paper metadata
-
○Scientific vocabulary similarity
Low similarity (3.8%) to scientific vocabulary
Repository
localization in computer vision = colliculus to predict accuracy + active vision through saccades
Basic Info
- Host: GitHub
- Owner: laurentperrinet
- License: gpl-3.0
- Language: Jupyter Notebook
- Default Branch: master
- Homepage: https://laurentperrinet.github.io/publication/dauce-20/
- Size: 606 MB
Statistics
- Stars: 4
- Watchers: 4
- Forks: 2
- Open Issues: 2
- Releases: 0
Metadata Files
README.md
WhereIsMyMNIST : a dual-pathway model for visual search
In a nutshell: localization in computer vision = colliculus to predict accuracy + active vision through saccades
Separating visual processing into a What and a Where pathways provides a strategy to model visual search. We developed a deep-learning based computational model in which the comparison of predicted accuracies from both pathways allows for efficient saccade selection.
Owner
- Name: Laurent Perrinet
- Login: laurentperrinet
- Kind: user
- Location: Marseille, France
- Company: Institut de Neurosciences de la Timone - AMU / CNRS
- Website: https://laurentperrinet.github.io
- Repositories: 116
- Profile: https://github.com/laurentperrinet
Researcher in Computational Neuroscience 🧠 and Machine Learning 💻 @ CNRS - Aix Marseille Université, France
GitHub Events
Total
- Watch event: 1
Last Year
- Watch event: 1