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Author Title Type [ Year(Asc)]
2024
Gené-Mola J, Ferrer-Ferrer M, Hemming J, Dalfsen P, Hoog D, Sanz-Cortiella R, et al.. AmodalAppleSize_RGB-D dataset: RGB-D images of apple trees annotated with modal and amodal segmentation masks for fruit detection, visibility and size estimation. Data in Brief. 2024;52.
Mayoral ICumplido, Vilaplana V, Gispert JD. BIOLOGICAL BRAIN-AGE PREDICTION USING MACHINE LEARNING ON NEUROIMAGING DATA: LINKS WITH PATHOPHYSIOLOGICAL MECHANISMS, DEMENTIA RISK FACTORS AND COGNITIVE DECLINE. Department of Experimental and Health Sciences (DCEXS), Universitat Pompeu Fabra. 2024.
Perez-Cano J, Valero ISansano, Anglada D, Pina O, Salembier P, Marqués F. Combining graph neural networks and computer vision methods for cell nuclei classification in lung tissue. Heliyon. 2024;10(7).  (4.05 MB)
Anglada D, Sala J, Marqués F, Salembier P, Pardàs M. Enhancing Ki-67 Cell Segmentation with Dual U-Net Models: A Step Towards Uncertainty-Informed Active Learning. In IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops. IEEE; 2024.  (838.72 KB)
Dios F, Torres-Benito S, Lázaro JAntonio, Casas J, Pinazo J, Lerín A. Experimental evaluation of a MIMO radar performance for ADAS application. Telecom. 2024;5(3):508-521.
Bonet D, Mas-Montserrat D, Giró-i-Nieto X, Ioannidis AG. HyperFast: Instant Classification for Tabular Data. In 38th Annual AAAI Conference on Artificial Intelligence (AAAI). 2024.  (3.15 MB)
Schürholt K. Hyper-Representations: Learning from Populations of Neural Networks. Mahoney M, Giró-i-Nieto X, Borth D. Unievrsity of St. Gallen. 2024.  (18.12 MB)
Pachón-García C, Hernandez C, Delicado P, Vilaplana V. SurvLIMEpy: A Python package implementing SurvLIME. Expert Systems With Applications. 2024;237, Part C.
2023
Barrabés M, Mas-Montserrat D, Geleta M, Giró-i-Nieto X, Ioannidis AG. Adversarial Learning for Feature Shift Detection and Correction. In Neural Information Processing Systems (NeurIPS). New Orleans, USA; 2023.
Cumplido-Mayoral I, García-Prat M, Operto G, Falcon C, Shekari M, Cacciaglia R, et al.. Biological Brain Age Prediction Using Machine Learning on Structural Neuroimaging Data: Multi-Cohort Validation Against Biomarkers of Alzheimer’s Disease and Neurodegeneration stratified by sex. eLife. 2023;12.
Cumplido-Mayoral I, Brugulat-Serrat A, Sánchez-Benavides G, González-Escalante A, Anastasi F, Mila-Aloma M, et al.. Brain-age mediates the association between modifiable risk factors and cognitive decline early in the AD continuum. In Alzheimer’s Association International Conference (AAIC). Amsterdam, Netherlands; 2023.
Cumplido-Mayoral I, Mila-Aloma M, Falcon C, Cacciaglia R, Minguillon C, Fauria K, et al.. Brain-age prediction and its associations with glial and synaptic CSF markers. In Alzheimer's Association International Conference. Amsterdam, Netherlands; 2023.
de-Mas-Giménez G, García-Gómez P, Casas J, Royo S. Gradient-Based Metrics for the Evaluation of Image Defogging. World Electric Vehicle Journal. 2023;14(9).  (4.92 MB)
Mosella-Montoro A. Graph Convolutional Neural Networks for 3D Data Analysis. Ruiz-Hidalgo J. Signal Theory and Communications. [Barcelona]: Universitat Politècnica de Catalunya; 2023.
Hernandez C, Pachón-García C, Delicado P, Vilaplana V. Interpreting Machine Learning models for Survival Analysis: A study of Cutaneous Melanoma using the SEER Database. In XAI-Healthcare 2023 Workshop at 21st International Conference of Artificial Intelligence in Medicine (AIME 2023). Portoroz, Slovenia; 2023.
Fernàndez D, Marqués F, Giró-i-Nieto X, Bou-Balust E. Knowledge graph population from news streams. Signal Theory and Communications. [Barcelona, Catalonia]: Universitat Politècnica de Catalunya; 2023.  (6.07 MB)

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