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Miguel López-Pérez
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2020 – today
- 2024
- [j10]Neel Kanwal
, Miguel López-Pérez
Are you sure it's an artifact? Artifact detection and uncertainty quantification in histological images. Comput. Medical Imaging Graph. 112: 102321 (2024) - [j9]Miguel López-Pérez
Learning from crowds for automated histopathological image segmentation. Comput. Medical Imaging Graph. 112: 102327 (2024) - [j8]Miguel López-Pérez, Alba Morquecho, Arne Schmidt, Fernando Pérez-Bueno, Aurelio Martín-Castro, Javier Mateos, Rafael Molina:
The CrowdGleason dataset: Learning the Gleason grade from crowds and experts. Comput. Methods Programs Biomed. 257: 108472 (2024) - [j7]Jose Pérez-Cano
An end-to-end approach to combine attention feature extraction and Gaussian Process models for deep multiple instance learning in CT hemorrhage detection. Expert Syst. Appl. 240: 122296 (2024) - [c3]Natalia P. García-de-la-Puente
Domain Adaptation for Unsupervised Cancer Detection: An Application for Skin Whole Slides Images from an Interhospital Dataset. MICCAI (4) 2024: 58-68 - 2023
- [j6]Miguel López-Pérez
Deep Gaussian Processes for Classification With Multiple Noisy Annotators. Application to Breast Cancer Tissue Classification. IEEE Access 11: 6922-6934 (2023) - [j5]Rocío del Amor
Annotation protocol and crowdsourcing multiple instance learning classification of skin histological images: The CR-AI4SkIN dataset. Artif. Intell. Medicine 145: 102686 (2023) - [c2]Miguel López-Pérez
Crowdsourcing Segmentation of Histopathological Images Using Annotations Provided by Medical Students. AIME 2023: 245-249 - 2022
- [j4]Miguel López-Pérez
Deep Gaussian processes for multiple instance learning: Application to CT intracranial hemorrhage detection. Comput. Methods Programs Biomed. 219: 106783 (2022) - 2021
- [j3]Miguel López-Pérez
A Contribution to Deep Learning Approaches for Automatic Classification of Volcano-Seismic Events: Deep Gaussian Processes. IEEE Trans. Geosci. Remote. Sens. 59(5): 3875-3890 (2021) - 2020
- [j2]Fernando Pérez-Bueno
A TV-based image processing framework for blind color deconvolution and classification of histological images. Digit. Signal Process. 101: 102727 (2020)
2010 – 2019
- 2019
- [j1]Ángel E. Esteban, Miguel López-Pérez
A new optical density granulometry-based descriptor for the classification of prostate histological images using shallow and deep Gaussian processes. Comput. Methods Programs Biomed. 178: 303-317 (2019) - [c1]Miguel López-Pérez
Classifying Prostate Histological Images Using Deep Gaussian Processes on a New Optical Density Granulometry-Based Descriptor. IDEAL (1) 2019: 39-46
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last updated on 2024-12-10 20:48 CET by the dblp team
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