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A
Górriz M. Active Deep Learning for Medical Imaging Segmentation. Giró-i-Nieto X, Carlier A, Faure E. 2017.  (2.84 MB)
Górriz M, Giró-i-Nieto X, Carlier A, Faure E. Active Deep Learning for Medical Imaging Segmentation. In Medical Image meets NIPS 2017 Workshop. 2017.  (187.43 KB)
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.
Combalia M, Podlipnik S, Hernandez C, García S, Ficapal J, Burgos J, et al.. Artificial intelligence to predict positivity of sentinel lymph node biopsy in melanoma patients. In European Association of Dermato Oncology (EADO 2022). 2022.
Luque J, Morros JR, Garde A, Anguita J, Farrús M, Macho D, et al.. Audio, Video and Multimodal Person Identification in a Smart Room. In CLEAR'06 Evaluation Campaign and Workshop - Classification of Events, Activities and Relationships. 2007. pp. 258–269.  (294.95 KB)
Luque J, Morros JR, Garde A, Anguita J, Farrús M, Macho D, et al.. Audio, Video and Multimodal Person Identification in a Smart Room. In Lecture notes in computer science - Multimodal Technologies for Perception of Humans. 2006. pp. 258–269.  (321.95 KB)
B
Wang L, Nie D, Li G, Puybareau E, Dolz J, Zhang Q, et al.. Benchmark on Automatic 6-month-old Infant Brain Segmentation Algorithms: The iSeg-2017 Challenge. IEEE Transactions on Medical Imaging. 2019;.
Ferran C, Casas J. Binary-Partition Tree creation using a quasi-inclusion criterion. In 8th International Conference on Information Visualization (IV04). 2004. pp. 259–264.
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. In Alzheimer's Association International Conference. 2022.
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.
Ferran C, Giró-i-Nieto X, Marqués F, Casas J. BPT Enhancement based on Syntactic and Semantic criteria. In Semantic Multimedia. Berlin / Heidelberg: Springer; 2006. pp. 184–198.
Ferran C, Giró-i-Nieto X, Marqués F, Casas J. BPT Enhancement based on Syntactic and Semantic criteria. In 1st International Conference on Semantic and Digital Media Technologies. 2006. pp. 184–198.
Cumplido-Mayoral I, Shekari M, Salvadó G, Operto G, Cacciaglia R, Falcon C, et al.. Brain structural alterations in cognitively unimpaired individuals with discordant amyloid-β PET and CSF Aβ42 status: findings using Machine Learning. In Alzheimer's Association International Conference. 2021.
Cumplido-Mayoral I, Shekari M, Salvadó G, Operto G, Cacciaglia R, Falcon C, et al.. Brain structural alterations in cognitively unimpaired individuals with discordant amyloid-β PET and CSF Aβ42 status: findings using Machine Learning. In Alzheimer's Association International Conference. 2021.
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.
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.
C
Poignant J, Budnik M, Bredin H, Barras C, Stefas M, Bruneau P, et al.. The CAMOMILE Collaborative Annotation Platform for Multi-modal, Multi-lingual and Multi-media Documents. In Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC 2016). Portorož (Slovenia); 2016.  (679.91 KB)
Petrone P, Casamitjana A, Falcon C, Artigues M, Operto G, Skouras S, et al.. Characteristic Brain Volumetric Changes in the AD Preclinical Signature. In Alzheimer's Association International Conference. Chicago, USA; 2018.
Petrone P, Casamitjana A, Falcon C, Artigues M, Operto G, Skouras S, et al.. Characteristic Brain Volumetric Changes in the AD Preclinical Signature. Alzheimer's & Dementia: The Journal of the Alzheimer's Association. 2018;14(7):P1235.
Fernàndez D. Clustering and Prediction of Adjective-Noun Pairs for Affective Computing. Campos V, Jou B, Giró-i-Nieto X, Chang S-F. 2016.  (10.38 MB)
Marqués F, Fioravanti S, Brigger P. Coding of image partitions by morphological skeleton using overlapping structuring elements. In IEEE WORKSHOP ON NONLINEAR SIGNAL AND IMAGE PROCESSING. 1995. pp. 250–253.
Sayrol E, Fischi O, Pardàs M. Color Inititialization for Lip Tracking. In International Conference on Augmented, Virtual Environments and 3D Imaging. 2001. pp. 351–354.
Fojo D, Campos V, Giró-i-Nieto X. Comparing Fixed and Adaptive Computation Time for Recurrent Neural Network. In International Conference on Learning Representations (ICLR). Vancouver, Canada; 2018.  (515.54 KB)
Górriz M, Giró-i-Nieto X, Carlier A, Faure E. Cost-Effective Active Learning for Melanoma Segmentation. In ML4H: Machine Learning for Health Workshop at NIPS 2017. Long Beach, CA, USA; 2017.  (521.82 KB)

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