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pro vyhledávání: '"Teixeira, Luis"'
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
This paper introduces ROSAR, a novel framework enhancing the robustness of deep learning object detection models tailored for side-scan sonar (SSS) images, generated by autonomous underwater vehicles using sonar sensors. By extending our prior work o
Externí odkaz:
http://arxiv.org/abs/2410.10554
Autor:
Gomes, Inês, Teixeira, Luís F., van Rijn, Jan N., Soares, Carlos, Restivo, André, Cunha, Luís, Santos, Moisés
The increasing use of deep learning across various domains highlights the importance of understanding the decision-making processes of these black-box models. Recent research focusing on the decision boundaries of deep classifiers, relies on generate
Externí odkaz:
http://arxiv.org/abs/2408.06302
3D human pose estimation aims to reconstruct the human skeleton of all the individuals in a scene by detecting several body joints. The creation of accurate and efficient methods is required for several real-world applications including animation, hu
Externí odkaz:
http://arxiv.org/abs/2407.03817
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
The increasing popularity of attention mechanisms in deep learning algorithms for computer vision and natural language processing made these models attractive to other research domains. In healthcare, there is a strong need for tools that may improve
Externí odkaz:
http://arxiv.org/abs/2204.12406
Autor:
Ali, Mohd Sajid, Teixeira, Luís M.C., Ramos, Maria J., Fernandes, Pedro A., Al-Lohedan, Hamad A.
Publikováno v:
In International Journal of Biological Macromolecules August 2024 274 Part 2
