Zobrazeno 1 - 10
of 10
pro vyhledávání: '"PATRÍCIO, CRISTIANO"'
The main challenges hindering the adoption of deep learning-based systems in clinical settings are the scarcity of annotated data and the lack of interpretability and trust in these systems. Concept Bottleneck Models (CBMs) offer inherent interpretab
Externí odkaz:
http://arxiv.org/abs/2411.05609
Autor:
Patrício, Cristiano, Barbano, Carlo Alberto, Fiandrotti, Attilio, Renzulli, Riccardo, Grangetto, Marco, Teixeira, Luis F., Neves, João C.
Contrastive Analysis (CA) regards the problem of identifying patterns in images that allow distinguishing between a background (BG) dataset (i.e. healthy subjects) and a target (TG) dataset (i.e. unhealthy subjects). Recent works on this topic rely o
Externí odkaz:
http://arxiv.org/abs/2406.00772
Concept-based models naturally lend themselves to the development of inherently interpretable skin lesion diagnosis, as medical experts make decisions based on a set of visual patterns of the lesion. Nevertheless, the development of these models depe
Externí odkaz:
http://arxiv.org/abs/2311.14339
Early detection of melanoma is crucial for preventing severe complications and increasing the chances of successful treatment. Existing deep learning approaches for melanoma skin lesion diagnosis are deemed black-box models, as they omit the rational
Externí odkaz:
http://arxiv.org/abs/2304.04579
The remarkable success of deep learning has prompted interest in its application to medical imaging diagnosis. Even though state-of-the-art deep learning models have achieved human-level accuracy on the classification of different types of medical da
Externí odkaz:
http://arxiv.org/abs/2205.04766
Autor:
Patrício, Cristiano, Neves, João
The recognition of unseen objects from a semantic representation or textual description, usually denoted as zero-shot learning, is more prone to be used in real-world scenarios when compared to traditional object recognition. Nevertheless, no work ha
Externí odkaz:
http://arxiv.org/abs/2110.04535
Autor:
PATRÍCIO, CRISTIANO1 patricio@ubi.pt, NEVES, JOÃO C.1 jcneves@di.ubi.pt, TEIXEIRA, LUÍS F.2 luisft@fe.up.pt
Publikováno v:
ACM Computing Surveys. Apr2024, Vol. 56 Issue 4, p1-41. 41p.
Autor:
Patrício, Cristiano, Neves, João C.
Publikováno v:
In Expert Systems With Applications January 2023 211
The remarkable success of deep learning has prompted interest in its application to medical imaging diagnosis. Even though state-of-the-art deep learning models have achieved human-level accuracy on the classification of different types of medical da
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b7f82f12ac765f6287a962cba661402e
Autor:
Patrício, Cristiano Pires
Publikováno v:
Repositório Científico de Acesso Aberto de Portugal
Repositório Científico de Acesso Aberto de Portugal (RCAAP)
instacron:RCAAP
Repositório Científico de Acesso Aberto de Portugal (RCAAP)
instacron:RCAAP
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Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______3056::d4ccdd536000b8458e12fce5a99bc3b3