Author

A. Ceia-Hasse

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Ecology· 3

Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Research Focus:ecology & biodiversity· 2 Research Focus:drug response / drug discovery· 1 Approach:machine learning (classical)· 1

Frequent Co-Authors

C. Capinha· 3 shared A. M. Kramer· 1 shared B. R. Gouveia· 1 shared C. A. Sousa· 1 shared C. Meijer· 1 shared C. Vila-Vicosa· 1 shared H. M. Pereira· 1 shared I. Jaric· 1 shared

Activity by Year

2020-2023 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 21 mutual co-author links

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3 shared papersEcology

C. Capinha

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

Predicting the timing of ecological phenomena across regions using citizen science data

C. Capinha, A. Ceia-Hasse, S. de-Miguel, C. Vila-Vicosa, M. Porto, I. Jaric, P. Tiago, N. Fernandez, J. Valdez, I. McCallum, H. M. Pereira

This paper introduces a framework to predict ecological event timing using citizen science data, showing accurate predictions for Japanese beetles and winter chanterelles across regions.

bioRxiv · May 5, 2023 · PreprintEcology

Forecasting the numbers of disease vectors with deep learning

A. Ceia-Hasse, C. A. Sousa, B. R. Gouveia, C. Capinha

This paper uses deep learning to forecast disease vector numbers, achieving high accuracy in predicting changes in Aedes aegypti egg counts.

bioRxiv · Nov 22, 2022 · PreprintEcology

Deep learning classification of temporal data in ecology

C. Capinha, A. Ceia-Hasse, A. M. Kramer, C. Meijer

This paper applies deep learning to classify ecological temporal data without manual feature extraction, showing improved accuracy across three ecological case studies.

bioRxiv · Sep 14, 2020Ecology