DNLM-IIFFT: An Implementation of the Deceived Non Local Means Filter Using Integral Images and the Fast Fourier Transform for a Reduced Computational Cost. - Saúl Calderón Ramírez; Manuel Zumbado Corrales (CIARP, 2017)

Automatic Calibration of the Deceived Non Local Means Filter for Improving the Segmentation of Cells in Fluorescence Based Microscopy. - Saúl Calderón Ramírez; Joel Barrantes; J. Schuster; Mauro Mendez; Jakub Begera (ICBEA, 2018)

Assessing the Impact of the Deceived Non Local Means Filter as a Preprocessing Stage in a Convolutional Neural Network Based Approach for Age Estimation Using Digital Hand X-Ray Images. - Saúl Calderón Ramírez; Fabian Fallas-Moya; Manuel Zumbado; Pascal N. Tyrrell; Hershel Stark; Ziga Emersic; Blaz Meden; Martín Solís (ICIP, 2018)

DNLM-MA-P: A Parallelization of the Deceived Non Local Means Filter with Moving Average and Symmetric Weighting. - Saúl Calderón Ramírez; Jorge Castro; Manuel Zurnbado (IWOBI, 2018)

Xylem Vessels Segmentation Through a Deep Learning Approach: a First Look. - Angel García-Pedrero; Ana Garcia-Cervigon; Cristina Caetano; Saúl Calderón Ramírez; Jose M. Olano; Consuelo Gonzalo-Martín; Mario Lillo-Saavedra; Miguel Garcia-Hidalgo (IWOBI, 2018)

Assessing the Impact of a Preprocessing Stage on Deep Learning Architectures for Breast Tumor Multi-class Classification with Histopathological Images. - Iván Calvo; Saúl Calderón Ramírez; Jordina Torrents-Barrena; Erick Muñoz; Domenec Puig (CARLA, 2019)

Insight GT: A Public, Fast, Web Image Ground Truth Authoring Tool. - Joel Barrantes-Garro; Hellen Rodríguez-Morales; Adrián Garnier-Artiñano; Saúl Calderón Ramírez; Fabian Porras-Jiménez; Luís Carlos Corrales-Arley; Ricardo Brenes-Camacho (CARLA, 2019)

Using Cluster Analysis to Assess the Impact of Dataset Heterogeneity on Deep Convolutional Network Accuracy: A First Glance. - Mauro Mendez; Saúl Calderón Ramírez; Pascal N. Tyrrell (CARLA, 2019)

A First Glance into Reversing Senescence on Herbarium Sample Images Through Conditional Generative Adversarial Networks. - Juan Villacis-Llobet; Marco Lucio-Troya; Marvin Calvo-Navarro; Saúl Calderón Ramírez; Erick Mata-Montero (CARLA, 2019)

Unsharp Masking Layer: Injecting Prior Knowledge in Convolutional Networks for Image Classification. - Jose Carranza-Rojas; Saúl Calderón Ramírez; Adán Mora-Fallas; Michael Granados-Menani; Jordina Torrents-Barrena (ICANN (3), 2019)

A Brief Analysis of U-Net and Mask R-CNN for Skin Lesion Segmentation. - Erick Alfaro; Ximena Bolaños Fonseca; Enrique M. Albornoz; César Ernesto Martínez; Saúl Calderón Ramírez (IWOBI, 2019)

Dealing with Scarce Labelled Data: Semi-supervised Deep Learning with Mix Match for Covid-19 Detection Using Chest X-ray Images. - Saúl Calderón Ramírez; Raghvendra Giri; Shengxiang Yang; Armaghan Moemeni; Mario Umaña; David A. Elizondo; Jordina Torrents-Barrena; Miguel A. Molina-Cabello (ICPR, 2020)

A First Glance to the Quality Assessment of Dental Photostimulable Phosphor Plates with Deep Learning. - Ariana Bermudez; Saúl Calderón Ramírez; Trevor Thang; Pascal N. Tyrrell; Armaghan Moemeni; Shengxiang Yang; Jordina Torrents-Barrena (IJCNN, 2020)

ML4H Auditing: From Paper to Practice. - Luis Oala; Jana Fehr; Luca Gilli; Pradeep Balachandran; Alixandro Werneck Leite; Saúl Calderón Ramírez; Danny Xie Li; Gabriel Nobis; Erick Alejandro Muñoz Alvarado; Giovanna Jaramillo-Gutierrez; Christian Matek; Arun Shroff; et al. (ML4H@NeurIPS, 2020)

MixMOOD: A systematic approach to class distribution mismatch in semi-supervised learning using deep dataset dissimilarity measures. - Saúl Calderón Ramírez; Luis Oala; Jordina Torrents-Barrena; Shengxiang Yang; Armaghan Moemeni; Wojciech Samek; Miguel A. Molina-Cabello (CoRR, 2020)

Convolutional neural networks for segmenting xylem vessels in stained cross-sectional images. - Angel García-Pedrero; Ana Garcia-Cervigon; Jose M. Olano; Miguel Garcia-Hidalgo; Mario Lillo-Saavedra; Consuelo Gonzalo-Martín; Cristina Caetano; Saúl Calderón Ramírez (Neural Comput. Appl., 2020)

Improving Uncertainty Estimations for Mammogram Classification using Semi-Supervised Learning. - Saúl Calderón Ramírez; Diego Murillo-Hernandez; Kevin Rojas-Salazar; Luis-Alexander Calvo-Valverde; Shengxiang Yang; Armaghan Moemeni; David A. Elizondo; Ezequiel López-Rubio; Miguel A. Molina-Cabello (IJCNN, 2021)

Enforcing Morphological Information in Fully Convolutional Networks to Improve Cell Instance Segmentation in Fluorescence Microscopy Images. - Willard Zamora-Cárdenas; Mauro Mendez; Saúl Calderón Ramírez; Martin Vargas; Gerardo Monge; Steve Quirós; David A. Elizondo; Jordina Torrents-Barrena; Miguel A. Molina-Cabello (IWANN (1), 2021)

Improving Uncertainty Estimation With Semi-Supervised Deep Learning for COVID-19 Detection Using Chest X-Ray Images. - Saúl Calderón Ramírez; Shengxiang Yang; Armaghan Moemeni; Simon Colreavy-Donnelly; David A. Elizondo; Luis Oala; Jorge Rodríguez-Capitán; Manuel Jiménez-Navarro; Ezequiel López-Rubio; Miguel A. Molina-Cabello (IEEE Access, 2021)

Correcting data imbalance for semi-supervised COVID-19 detection using X-ray chest images. - Saúl Calderón Ramírez; Shengxiang Yang; Armaghan Moemeni; David A. Elizondo; Simon Colreavy-Donnelly; Luis Fernando Chavarria-Estrada; Miguel A. Molina-Cabello (Appl. Soft Comput., 2021)

More Than Meets The Eye: Semi-supervised Learning Under Non-IID Data. - Saúl Calderón Ramírez; Luis Oala (CoRR, 2021)

Enforcing Morphological Information in Fully Convolutional Networks to Improve Cell Instance Segmentation in Fluorescence Microscopy Images. - Willard Zamora-Cárdenas; Mauro Mendez; Saúl Calderón Ramírez; Martin Vargas; Gerardo Monge; Steve Quirós; David A. Elizondo; Miguel A. Molina-Cabello (CoRR, 2021)

A Real Use Case of Semi-Supervised Learning for Mammogram Classification in a Local Clinic of Costa Rica. - Saúl Calderón Ramírez; Diego Murillo-Hernandez; Kevin Rojas-Salazar; David A. Elizondo; Shengxiang Yang; Miguel A. Molina-Cabello (CoRR, 2021)

Machine Learning for Health: Algorithm Auditing & Quality Control. - Luis Oala; Andrew G. Murchison; Pradeep Balachandran; Shruti Choudhary; Jana Fehr; Alixandro Werneck Leite; Peter G. Goldschmidt; Christian Johner; Elora D. M. Schörverth; Rose Nakasi; Martin Meyer; Federico Cabitza; et al. (J. Medical Syst., 2021)

Feature Density as an Uncertainty Estimator Method in the Binary Classification Mammography Images Task for a Supervised Deep Learning Model. - Ricardo Javier Fuentes-Fino; Saúl Calderón Ramírez; Enrique Domínguez; Ezequiel López-Rubio; Marco A. Hernandez-Vasquez; Miguel A. Molina-Cabello (IWBBIO (2), 2022)

Dealing with distribution mismatch in semi-supervised deep learning for COVID-19 detection using chest X-ray images: A novel approach using feature densities. - Saúl Calderón Ramírez; Shengxiang Yang; David A. Elizondo; Armaghan Moemeni (Appl. Soft Comput., 2022)

Semi-supervised Deep Learning for Image Classification with Distribution Mismatch: A Survey. - Saúl Calderón Ramírez; Shengxiang Yang; David A. Elizondo (CoRR, 2022)

Improving Semi-supervised Deep Learning by using Automatic Thresholding to Deal with Out of Distribution Data for COVID-19 Detection using Chest X-ray Images. - Isaac Benavides-Mata; Saúl Calderón Ramírez (CoRR, 2022)

A real use case of semi-supervised learning for mammogram classification in a local clinic of Costa Rica. - Saúl Calderón Ramírez; Diego Murillo-Hernandez; Kevin Rojas-Salazar; David A. Elizondo; Shengxiang Yang; Armaghan Moemeni; Miguel A. Molina-Cabello (Medical Biol. Eng. Comput., 2022)

Semisupervised Deep Learning for Image Classification With Distribution Mismatch: A Survey. - Saúl Calderón Ramírez; Shengxiang Yang; David A. Elizondo (IEEE Trans. Artif. Intell., 2022)

Object Detection in Pineapple Fields Drone Imagery Using Few Shot Learning and the Segment Anything Model. - Fabian Fallas-Moya; Saúl Calderón Ramírez; Amir Sadovnik; Hairong Qi 001 (ICMLA, 2023)

A Novel Dataset for Financial Education Text Simplification in Spanish. - Nelson Perez-Rojas; Saúl Calderón Ramírez; Martin Solis-Salazar; Mario Romero-Sandoval; Monica Arias-Monge; Horacio Saggion (CoRR, 2023)

Dataset Similarity to Assess Semisupervised Learning Under Distribution Mismatch Between the Labeled and Unlabeled Datasets. - Saúl Calderón Ramírez; Luis Oala; Jordina Torrents-Barrena; Shengxiang Yang; David A. Elizondo; Armaghan Moemeni; Simon Colreavy-Donnelly; Wojciech Samek; Miguel A. Molina-Cabello; Ezequiel López-Rubio (IEEE Trans. Artif. Intell., 2023)

An uncertainty estimator method based on the application of feature density to classify mammograms for breast cancer detection. - Ricardo Javier Fuentes-Fino; Saúl Calderón Ramírez; Enrique Domínguez; Ezequiel López-Rubio; David A. Elizondo; Miguel A. Molina-Cabello (Neural Comput. Appl., 2023)

The BEA 2024 Shared Task on the Multilingual Lexical Simplification Pipeline. - Matthew Shardlow; Fernando Alva-Manchego; Riza Batista-Navarro; Stefan Bott; Saúl Calderón Ramírez; Rémi Cardon; Thomas François; Akio Hayakawa; Andrea Horbach; Anna Hülsing; Yusuke Ide; Joseph Marvin Imperial; et al. (BEA, 2024)

Uncertainty Estimation in Large Language Models to Support Biodiversity Conservation. - Maria Mora-Cross; Saúl Calderón Ramírez (NAACL (Industry Track), 2024)

Enhancing Object Segmentation via Few-Shot Learning with Limited Annotated Data. - Iván García Aguilar; Syed Ali Haider Jafri; David A. Elizondo; Saúl Calderón Ramírez; Sarah Greenfield; Rafael M. Luque-Baena (SOCO (2), 2024)

MultiLS-SP/CA: Lexical Complexity Prediction and Lexical Simplification Resources for Catalan and Spanish. - Stefan Bott; Horacio Saggion; Nelson Perez-Rojas; Martin Solis-Salazar; Saúl Calderón Ramírez (CoRR, 2024)

A Novel Spanish Dataset for Financial Education Text Simplification Targeting Visually Impaired Individuals. - Nelson Perez-Rojas; Saúl Calderón Ramírez; Martín Solís; Mario Romero-Sandoval; Monica Arias-Monge; Horacio Saggion (IEEE Access, 2025)