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] . Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the BRATS challenge. In MICCAI - Multimodal Brain Tumor Segmentation Challenge. 2018.
. Deep learning-based methodology for smoke plume segmentation of wildfire images. In 14th International Symposium on Fire Safety Science (IAFSS2023). Tsukuba, Japan: International Association for Fire Safety Science (IAFSS); 2023.
. The segmentation of images via scale-space trees. In British Machine Vision Conference. Southampton, UK; 1998. pp. 33–43. 
(1.18 MB)
(1.18 MB). New interaction modes for rich panoramic live video experiences. Behaviour & Information Technology. 2014;33(8). (278.16 KB)
(278.16 KB). Machine Learning for Genomic Sequence Processing. . 2022 .
. Adversarial Learning for Feature Shift Detection and Correction. In Neural Information Processing Systems (NeurIPS). New Orleans, USA; 2023.
. Advances in Biomedical Missing Data Imputation: A Survey. IEEE Access. 2024;.
. 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)
(1.17 MB). 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)
(700.25 KB). 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)
(4.3 MB). 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)
(317 KB). 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)
(217.39 KB). 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.
. Efficient Combination of Pairwise Feature Networks. In: . Neural Connectomics Challenge. Springer International Publishing; 2017.
. Study of Gene Regulatory Networks Inference Methods from Gene Expression Data. . 2017. (2.73 MB)
(2.73 MB). NetBenchmark: a bioconductor package for reproducible benchmarks of gene regulatory network inference. BMC Bioinformatics. 2015;16. (851.49 KB)
(851.49 KB). Efficient search of objects in images using deep reinforcement learning. NIPS Women in Machine Learning Workshop. Barcelona.; 2016.
. Budget-aware Semi-Supervised Semantic and Instance Segmentation. In CVPR 2019 DeepVision Workshop. Long Beach, CA, USA: OpenCVF; 2019. (6.59 MB)
(6.59 MB). Efficient Exploration of Region Hierarchies for Semantic Segmentation. . 2015. (11.62 MB)
(11.62 MB). Detection-aided medical image segmentation using deep learning. . 2017. (7.07 MB)
(7.07 MB). Detection-aided liver lesion segmentation using deep learning. In ML4H: Machine Learning for Health Workshop at NIPS 2017. 2017. (1 MB)
(1 MB). Image and Video Object Segmentation in Low Supervision Scenarios. . Computer Architectures. [Barcelona]: Universitat Politecnica de Catalunya; 2021.
. Hierarchical Object Detection with Deep Reinforcement Learning. In Deep Learning for Image Processing Applications. Amsterdam, The Netherlands: IOS Press; 2017.