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Bernal O, Mas-Montserrat D, Giró-i-Nieto X, Ioannidis AG. SALAI-Net: species-agnostic local ancestry inference network. Bioinformatics. 2022;38.
Benitez AB, Martinez JM, Rising H, Salembier P. Description of a Single Multimedia Document. In Introduction to the mpeg-7: multimedia content description interface. B. S. Manjunath, P. Salembier, T. Sikora (Eds.). Wiley; 2002. pp. 111–138.
Benediktsson J, Bruzzone L, Chanussot J, Dalla Mura M, Salembier P, Valero S. Hierarchical analysis of remote sensing data: morphological attribute profiles and binary partition trees. In International Symposium on Mathematical Morphology 2011. Intra, Lake Maggiore, Italy; 2011. pp. 306–319.  (394.77 KB)
Bellver-Bueno M, Ventura C, Silberer C, Kazakos I, Torres J, Giró-i-Nieto X. RefVOS: A Closer Look at Referring Expressions for Video Object Segmentation. Multimedia Tools and Applications. 2022;.  (5.78 MB)
Bellver M, Giró-i-Nieto X, Marqués F. Efficient search of objects in images using deep reinforcement learning. NIPS Women in Machine Learning Workshop. Barcelona.; 2016.
Bellver M, Salvador A, Torres J, Giró-i-Nieto X. Budget-aware Semi-Supervised Semantic and Instance Segmentation. In CVPR 2019 DeepVision Workshop. Long Beach, CA, USA: OpenCVF; 2019.  (6.59 MB)
Bellver M. Efficient Exploration of Region Hierarchies for Semantic Segmentation. Ventura C, Giró-i-Nieto X. 2015.  (11.62 MB)
Bellver M. Detection-aided medical image segmentation using deep learning. Maninis K-K, Pont-Tuset J, van Gool L, Giró-i-Nieto X, Torres J. 2017.  (7.07 MB)
Bellver M, Maninis K-K, Pont-Tuset J, Torres J, Giró-i-Nieto X, van Gool L. Detection-aided liver lesion segmentation using deep learning. In ML4H: Machine Learning for Health Workshop at NIPS 2017. 2017.  (1 MB)
Bellver M, Giró-i-Nieto X, Marqués F, Torres J. Hierarchical Object Detection with Deep Reinforcement Learning. In Deep Learning for Image Processing Applications. Amsterdam, The Netherlands: IOS Press; 2017.
Bellver M. Image and Video Object Segmentation in Low Supervision Scenarios. Torres J, Giró-i-Nieto X. Computer Architectures. [Barcelona]: Universitat Politecnica de Catalunya; 2021.
Bellver M, Salvador A, Torres J, Giró-i-Nieto X. Mask-guided sample selection for Semi-Supervised Instance Segmentation. Multimedia Tools and Applications. 2020;.  (2.2 MB)
Bellver M, Giró-i-Nieto X, Marqués F, Torres J. Hierarchical Object Detection with Deep Reinforcement Learning. In Deep Reinforcement Learning Workshop, NIPS 2016. 2016.  (877.51 KB)
Bellot P, Salembier P, Oliveras A, Meyer PE. Study of Normalization and Aggregation Approaches for Consensus Network Estimation. In 2015 IEEE Symposium Series on Computational Intelligence: IEEE Symposium on Artificial Life (2015 IEEE ALIFE). Cape Town, South Africa; 2015.  (317 KB)
Bellot P, Meyer PE. Efficient combination of pairwise feature networks. JMLR: Workshop and Conference Proceedings . Nancy, France: JMLR: Workshop and Conference Proceedings; 2014;46:77 - 84.  (217.39 KB)
Bellot P, Salembier P, Pham NC, Meyer PE. Unsupervised GRN Ensemble. In Sanguinetti G., Huynh-Thu V. (eds) Methods in Molecular Biology . New York, NY: Springer science, Humana Press; 2019. pp. 283-302.
Bellot P. Study of Gene Regulatory Networks Inference Methods from Gene Expression Data. Salembier P. 2017.  (2.73 MB)
Bellot P, Meyer P. Efficient Combination of Pairwise Feature Networks. In: Battaglia D, Guyon I, Lemaire V, Orlandi J, Ray B, Soriano J. Neural Connectomics Challenge. Springer International Publishing; 2017.
Bellot P, Olsen C, Salembier P, Oliveras A, Meyer PE. NetBenchmark: a bioconductor package for reproducible benchmarks of gene regulatory network inference. BMC Bioinformatics. 2015;16.  (851.49 KB)
Bazazian D, Casas J, Ruiz-Hidalgo J. Fast and Robust Edge Extraction in Unorganized Point Clouds. In International Conference on Digital Image Computing: Techniques and Applications. Adelaide, Australia: DICTA/IEEE; 2015.  (700.25 KB)
Bazazian D, Casas J, Ruiz-Hidalgo J. Segmentation-based Multi-Scale Edge Extraction to Measure the Persistence of Features in Unorganized Point Clouds. In International Conference on Computer Vision Theory and Applications. Porto, Portugal; 2017.  (4.3 MB)
Batiste G. Generative Adversarial Networks for Anomaly Detection in Images. Vilaplana V. 2018.
Bartusiak E, Barrabés M, Rymbe A, Gimbernat J, López C, Barberis L, et al.. Predicting Dog Phenotypes from Genotypes. In 44th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC'22). 2022.  (1.17 MB)
Barrabés M. Machine Learning for Genomic Sequence Processing. Mas-Montserrat D, Giró-i-Nieto X, Ioannidis AG. 2022 .
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; In Press.

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