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The Algonauts Project 2023 Challenge: UARK-UAlbany Team Solution

The Algonauts Project 2023 Challenge: UARK-UAlbany Team Solution

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2844927888

The Algonauts Project 2023 Challenge: UARK-UAlbany Team Solution

About this item

Full title

The Algonauts Project 2023 Challenge: UARK-UAlbany Team Solution

Publisher

Ithaca: Cornell University Library, arXiv.org

Journal title

arXiv.org, 2023-08

Language

English

Formats

Publication information

Publisher

Ithaca: Cornell University Library, arXiv.org

More information

Scope and Contents

Contents

This work presents our solutions to the Algonauts Project 2023 Challenge. The primary objective of the challenge revolves around employing computational models to anticipate brain responses captured during participants' observation of intricate natural visual scenes. The goal is to predict brain responses across the entire visual brain, as it is the region where the most reliable responses to images have been observed. We constructed an image-based brain encoder through a two-step training process to tackle this challenge. Initially, we created a pretrained encoder using data from all subjects. Next, we proceeded to fine-tune individual subjects. Each step employed different training strategies, such as different loss functions and objectives, to introduce diversity. Ultimately, our solution constitutes an ensemble of multiple unique encoders. The code is available at https://github.com/uark-cviu/Algonauts2023...

Alternative Titles

Full title

The Algonauts Project 2023 Challenge: UARK-UAlbany Team Solution

Authors, Artists and Contributors

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_proquest_journals_2844927888

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2844927888

Other Identifiers

E-ISSN

2331-8422

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