ProtoAL: interpretable deep active learning with prototypes for medical imaging (2024)
- Authors:
- USP affiliated authors: CARVALHO, ANDRÉ CARLOS PONCE DE LEON FERREIRA DE - ICMC ; SANTOS, IURY BATISTA DE ANDRADE - ICMC
- Unidade: ICMC
- Subjects: APRENDIZAGEM PROFUNDA; DIAGNÓSTICO POR COMPUTADOR; DIAGNÓSTICO POR IMAGEM
- Keywords: Deep Active Learning; Interpretability; Medical Imaging
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Source:
- Título: Proceedings
- ISSN: 1613-0073
- Conference titles: European Conference on Artificial Intelligence - ECAI
-
ABNT
SANTOS, Iury Batista de Andrade e CARVALHO, Andre Carlos Ponce de Leon Ferreira de. ProtoAL: interpretable deep active learning with prototypes for medical imaging. 2024, Anais.. Aachen: CEUR-WS, 2024. Disponível em: https://ceur-ws.org/Vol-3831/paper2.pdf. Acesso em: 29 dez. 2025. -
APA
Santos, I. B. de A., & Carvalho, A. C. P. de L. F. de. (2024). ProtoAL: interpretable deep active learning with prototypes for medical imaging. In Proceedings. Aachen: CEUR-WS. Recuperado de https://ceur-ws.org/Vol-3831/paper2.pdf -
NLM
Santos IB de A, Carvalho ACP de LF de. ProtoAL: interpretable deep active learning with prototypes for medical imaging [Internet]. Proceedings. 2024 ;[citado 2025 dez. 29 ] Available from: https://ceur-ws.org/Vol-3831/paper2.pdf -
Vancouver
Santos IB de A, Carvalho ACP de LF de. ProtoAL: interpretable deep active learning with prototypes for medical imaging [Internet]. Proceedings. 2024 ;[citado 2025 dez. 29 ] Available from: https://ceur-ws.org/Vol-3831/paper2.pdf - Neural architecture search with interpretable meta-features and fast predictors
- Aprendizado por reforço profundo para navegação visual semântica com memória
- Deep reinforcement learning for visual semantic navigation with memory
- A deep reinforcement learning approach with visual semantic navigation with memory for mobile robots in indoor home context
- Explainable machine learning for breast cancer diagnosis
- Reduction strategies for hierarchical multi-label classification in protein function prediction
- Intelligent-guided adaptive search for the maximum covering location problem
- Clus-DTI: improving decision-tree classification with a clustering-based decision-tree induction algorithm
- A density-based clustering approach for behavior change detection in data streams
- Automatic selection of learning bias for active sampling
Download do texto completo
| Tipo | Nome | Link | |
|---|---|---|---|
 |
3222466.pdf | Direct link |
How to cite
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
