João A. M. Santos

Publication Activity (10 Years)

Years Active: 2012-2024
Publications (10 Years): 27

Top Topics

Nearest Neighbour

Imbalanced Datasets

Top Venues

Artif. Intell. Rev.

Publications

João A. M. Santos, Miguel S. E. Martins, Rui M. Pinto, Susana M. Vieira
Towards Sustainable Inventory Management: A Many-Objective Approach to Stock Optimization in Multi-Storage Supply Chains. Algorithms 17 (6) (2024)
Miriam Seoane Santos, Pedro Henriques Abreu, Nathalie Japkowicz, Alberto Fernández, João A. M. Santos
A unifying view of class overlap and imbalance: Key concepts, multi-view panorama, and open avenues for research. Inf. Fusion 89 (2023)
José Pereira Amorim, Pedro Henriques Abreu, João A. M. Santos, Henning Müller
Evaluating Post-hoc Interpretability with Intrinsic Interpretability. CoRR (2023)
José Pereira Amorim, Pedro H. Abreu, João A. M. Santos, Marc Cortes, Victor Vila
Evaluating the faithfulness of saliency maps in explaining deep learning models using realistic perturbations. Inf. Process. Manag. 60 (2) (2023)
Miriam Seoane Santos, Pedro Henriques Abreu, Nathalie Japkowicz, Alberto Fernández, Carlos Soares, Szymon Wilk, João A. M. Santos
On the joint-effect of class imbalance and overlap: a critical review. Artif. Intell. Rev. 55 (8) (2022)
Miriam Seoane Santos, Pedro Henriques Abreu, Alberto Fernández, Julián Luengo, João A. M. Santos
The impact of heterogeneous distance functions on missing data imputation and classification performance. Eng. Appl. Artif. Intell. 111 (2022)
João A. M. Santos, João M. C. Sousa, Susana M. Vieira, André F. Ferreira
Many-objective optimization of a three-echelon supply chain: A case study in the pharmaceutical industry. Comput. Ind. Eng. 173 (2022)
Jorge Ferreira, Inês Domingues, Olga Sousa, Inês Sampaio, João A. M. Santos
Classification of oesophagic early-stage cancers: deep learning versus traditional learning approaches. BIBE (2020)
Inês Domingues, Gisèle Pereira, Pedro Martins, Hugo Duarte, João A. M. Santos, Pedro Henriques Abreu
Using deep learning techniques in medical imaging: a systematic review of applications on CT and PET. Artif. Intell. Rev. 53 (6) (2020)
Miriam Seoane Santos, Pedro Henriques Abreu, Szymon Wilk, João A. M. Santos
How distance metrics influence missing data imputation with k-nearest neighbours. Pattern Recognit. Lett. 136 (2020)
José Pereira Amorim, Pedro H. Abreu, Mauricio Reyes, João A. M. Santos
Interpretability vs. Complexity: The Friction in Deep Neural Networks. IJCNN (2020)
Miriam Seoane Santos, Pedro H. Abreu, Szymon Wilk, João A. M. Santos
Assessing the Impact of Distance Functions on K-Nearest Neighbours Imputation of Biomedical Datasets. AIME (2020)
Miriam Seoane Santos, Ricardo Cardoso Pereira, Adriana Fonseca Costa, Jastin Pompeu Soares, João A. M. Santos, Pedro Henriques Abreu
Generating Synthetic Missing Data: A Review by Missing Mechanism. IEEE Access 7 (2019)
Ana Catarina Oliveira, Inês Domingues, Hugo Duarte, João A. M. Santos, Pedro H. Abreu
Going Back to Basics on Volumetric Segmentation of the Lungs in CT: A Fully Image Processing Based Technique. IbPRIA (2) (2019)
Inês Domingues, Inês Sampaio, Hugo Duarte, João A. M. Santos, Pedro H. Abreu
Computer Vision in Esophageal Cancer: A Literature Review. IEEE Access 7 (2019)
Gabriel Silva, Inês Domingues, Hugo Duarte, João A. M. Santos
Automatic Generation of Lymphoma Post-Treatment PETs using Conditional-GANs. DICTA (2019)
Francisco Marques, Hugo Duarte, João A. M. Santos, Inês Domingues, José Pereira Amorim, Pedro H. Abreu
An iterative oversampling approach for ordinal classification. SAC (2019)
Miriam Seoane Santos, Jastin Pompeu Soares, Pedro Henriques Abreu, Hélder Araújo, João A. M. Santos
Cross-Validation for Imbalanced Datasets: Avoiding Overoptimistic and Overfitting Approaches [Research Frontier]. IEEE Comput. Intell. Mag. 13 (4) (2018)
Gisèle Pereira, Inês Domingues, Pedro Martins, Pedro H. Abreu, Hugo Duarte, João A. M. Santos
Registration of CT with PET: A Comparison of Intensity-Based Approaches. IWCIA (2018)
Marta Mercier, Miriam Seoane Santos, Pedro H. Abreu, Carlos Soares, Jastin Pompeu Soares, João A. M. Santos
Analysing the Footprint of Classifiers in Overlapped and Imbalanced Contexts. IDA (2018)
Jastin Pompeu Soares, Miriam Seoane Santos, Pedro Henriques Abreu, Hélder Araújo, João A. M. Santos
Exploring the Effects of Data Distribution in Missing Data Imputation. IDA (2018)
José Pereira Amorim, Inês Domingues, Pedro Henriques Abreu, João A. M. Santos
Interpreting deep learning models for ordinal problems. ESANN (2018)
Inês Domingues, Pedro H. Abreu, João A. M. Santos
Bi-Rads Classification of Breast Cancer: A New Pre-Processing Pipeline for Deep Models Training. ICIP (2018)
Inês Domingues, José Pereira Amorim, Pedro H. Abreu, Hugo Duarte, João A. M. Santos
Evaluation of Oversampling Data Balancing Techniques in the Context of Ordinal Classification. IJCNN (2018)
Miriam Seoane Santos, Jastin Pompeu Soares, Pedro Henriques Abreu, Hélder Araújo, João A. M. Santos
Influence of Data Distribution in Missing Data Imputation. AIME (2017)
Mariana A. Nogueira, Pedro Henriques Abreu, Pedro Martins, Penousal Machado, Hugo Duarte, João A. M. Santos
An artificial neural networks approach for assessment treatment response in oncological patients using PET/CT images. BMC Medical Imaging 17 (1) (2017)
Mariana A. Nogueira, Pedro Henriques Abreu, Pedro Martins, Penousal Machado, Hugo Duarte, João A. M. Santos
Image descriptors in radiology images: a systematic review. Artif. Intell. Rev. 47 (4) (2017)
João A. M. Santos, Rui Abreu
Lightweight Automatic Error Detection by Monitoring Collar Variables. ICTSS (2012)