Search Publication

Export 48 results:
[ Author(Asc)] Title Type Year
Filters: First Letter Of Last Name is B  [Clear All Filters]
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z 
B
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 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)
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. Efficient Exploration of Region Hierarchies for Semantic Segmentation. Ventura C, Giró-i-Nieto X. 2015.  (11.62 MB)
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, 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, 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. 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)
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, 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, 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, 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)
Bellot P. Study of Gene Regulatory Networks Inference Methods from Gene Expression Data. Salembier P. 2017.  (2.73 MB)
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)
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.
Barkhuus L, Zoric G, Engström A, Ruiz-Hidalgo J, Verzijp N. New interaction modes for rich panoramic live video experiences. Behaviour & Information Technology. 2014;33(8).
Bangham J, Ruiz-Hidalgo J, Harvey R, Cawley G. The segmentation of images via scale-space trees. In British Machine Vision Conference. Southampton, UK; 1998. pp. 33–43.  (1.18 MB)
Balibrea M. Deep learning for semantic segmentation of airplane hyperspectral imaging. Salgueiro L, Vilaplana V. 2019.
Bakas S, Reyes M, Jakab A, Bauer S, Casamitjana A, Vilaplana V, et al.. 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.
Bach M, Thiran J, Marqués F. How can physicians quantify brain degeneration?. In: Dutoit T, Marqués F. Applied signal processing. 2009. pp. 411–449.

Pages