Search Publication

Export 1101 results:
[ Author(Desc)] Title Type Year
Filters: Filter is   [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 
F
Fernàndez D, Bou E, Giró-i-Nieto X. VLX-Stories: a Semantically Linked Event platform for media publishers. In Proceedings of the ISWC 2019 Satellite Tracks (Posters & Demonstrations, Industry, and Outrageous Ideas) co-located with 18th International Semantic Web Conference (ISWC 2019). Auckland, New Zealand: CEUR Workshop Proceeedings; 2019.  (759.51 KB)
Fernàndez D, Woodward A, Campos V, Jou B, Giró-i-Nieto X, Chang S-F. More cat than cute? Interpretable Prediction of Adjective-Noun Pairs. In ACM Multimedia 2017 Workshop on Multimodal Understanding of Social, Affective and Subjective Attributes. Mountain View, CA (USA): ACM SIGMM; 2017.  (9.62 MB)
Fernàndez D, Bou-Balust E, Giró-i-Nieto X. Linking Media: adopting Semantic Technologies for multimodal media connection. In International Semantic Web Conference - ISWC (Industry Track). Monterey, CA, USA; 2018.  (265.23 KB)
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.
Ferran C, Casas J. Object representation using colour, shape and structure criteria in a Binary Partition Tree. In IEEE International Conference on Image Processing. 2005.
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.
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.
Ferrarons-Betrian M. Mobile Visual Search at Catchoom. Adamek T, Giró-i-Nieto X. 2014.
Ferrer-Ferrer M, Ruiz-Hidalgo J, Gregorio E, Vilaplana V, Morros JR, Gené-Mola J. Simultaneous Fruit Detection and Size Estimation Using Multitask Deep Neural Networks  . Biosystems Engineering. 2023;233:63-75.  (10.36 MB)
Ferri A. Object Tracking in Video with TensorFlow. Giró-i-Nieto X, Torres J, Salvador A. 2016.  (22.63 MB)
Figueras P, Haas C, Capdevila C, Vilaplana V. Las Mancomunidades en España. Boletí de la Asociación de Geógrafos Españoles. 2005;:151–176.
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)
Fojo D. Reproducing and Analyzing Adaptive Computation Time in PyTorch and TensorFlow. Campos V, Giró-i-Nieto X. 2018.  (1.41 MB)
Fontdevila-Bosch E. Region-oriented Convolutional Networks for Object Retrieval. Salvador A, Giró-i-Nieto X. 2015.  (8.02 MB)
Frias-Velazquez A, Morros JR. Histogram computation based on image bitwise decomposition. In ICIP 2009. 2009.
Frias-Velazquez A, Morros JR, García M, Philips W. Hierarchical stack filtering: a bitplane-based algorithm for massively parallel processors. Journal of Real-Time Image Processing. 2017;.  (868.82 KB)
Frias-Velazquez A, Morros JR. Gray-scale erosion algorithm based on image bitwise decomposition: application to focal plane processors. In IEEE International Conference on Acoustics, Speech and Signal Processing 2009. 2009. pp. 845–848.
G
Gallego J. Parametric Region-Based Foreground Segmentation in Planar and Multi-View Sequences. Pardàs M. Universitat Politècnica de Catalunya (UPC); 2013.  (70.23 MB)
Gallego J, Pardàs M, Haro G. Bayesian foreground segmentation and tracking using pixel-wise background model and region-based foreground model. In 16th IEEE International Conference on Image Processing. 2009. pp. 3205–3208.
Gallego J, Pardàs M, Solano M. Foreground objects segmentation for moving camera scenarios based on SCGMM. In Computational Intelligence for Multimedia Understanding. Berlin Heidelberg: Springer; 2012. pp. 195-206.
Gallego J, Pardàs M. Segmentation and Tracking of Static and Moving Objects in Video Surveillance Scenarios. In IEEE International Conference on Image Processing. 2008. pp. 2716–2719.
Gallego J, Pardàs M, Haro G. Enhanced foreground segmentation and tracking combining Bayesian background, shadow and foreground modeling. Pattern Recognition Letters. 2012;33(12):1558–1568.
Gallego J, Pardàs M. Multiview Foreground Segmentation using 3D Probabilistic Model. In ICIP, IEEE International Conference on Image Processing. 2014.  (2.38 MB)
Gallego J, Pardàs M. Enhanced bayesian foreground segmentation using brightness and color distortion region-based model for shadow removal. In 2010 IEEE International Conference on Image Processing. 2010. pp. 3449–3452.
Gallego J, Pardàs M. Robust 3D SFS reconstruction based on reliability maps. In ICIP, IEEE International Conference on Image Processing. 2014.  (7.46 MB)

Pages