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Pachón-García C, Hernandez C, Delicado P, Vilaplana V. SurvLIMEpy: A Python package implementing SurvLIME. Expert Systems With Applications. 2024;237, Part C.
Palou G, Salembier P. Precision-Recall-Classification Evaluation Framework: Application to Depth Estimation on Single Images. In European Conference on Computer Vision (ECCV). Zurich; 2014.  (1.37 MB)
Palou G, Salembier P. Depth Ordering on Image Sequences Using Motion Occlusions. In IEEE Int. Conf. in Image Processing, ICIP 2012. Orlando, Florida, USA; 2012.  (5.42 MB)
Palou G, Salembier P. Monocular Depth Ordering Using T-junctions and Convexity Occlusion Cues. IEEE Transactions on Image Processing. 2013;22(5): 1926 - 1939 .  (2.64 MB)
Palou G, Salembier P. Occlusion-based depth ordering on monocular images with binary partition tree. In IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2011. Prague, Czech Republic; 2011. pp. 1093–1096.  (444.04 KB)
Palou G, Salembier P. From local occlusion cues to global depth estimation. In IEEE Int. Conf. on Acoustics Speech and Signal Processing, ICASSP 2012. Kyoto, Japan; 2012.  (480.32 KB)
Palou G, Salembier P. Depth order estimation for video frames using motion occlusions. IET Computer Vision. 2014;8(2):152-160.  (910.25 KB)
Palou G, Salembier P. Hierarchical Video Representation with Trajectory Binary Partition Tree. In Computer Vision and Pattern Recognition (CVPR). Portland, Oregon; 2013.  (4.69 MB)
Palou G. Monocular Depth Estimation in Images and Sequences using Occlusion Cues. Salembier P. Signal Theory and Communications. 2014. p. 250.  (107.61 MB)
Palou G, Salembier P. Monocular Depth Ordering Using Occlusion Cues. Barcelona: Technical University of Catalonia; 2011 .
Palou G, Salembier P. 2.1 Depth Estimation of Frames in Image Sequences Using Motion Occlusions. In Computer Vision – ECCV 2012. Workshops and Demonstrations. Springer Berlin Heidelberg; 2012.  (8.88 MB)
Pan J, Giró-i-Nieto X. End-to-end Convolutional Network for Saliency Prediction. Large-scale Scene Understanding Challenge (LSUN) at CVPR Workshops . Boston, MA (USA): arXiv; 2015 .  (1.18 MB)
Pan J, Canton-Ferrer C, McGuinness K, O'Connor N, Torres J, Sayrol E, et al.. SalGAN: Visual Saliency Prediction with Generative Adversarial Networks. In CVPR 2017 Scene Understanding Workshop (SUNw). Honolulu, Hawaii, USA; 2017.  (1.85 MB)
Pan J. Visual Saliency Prediction using Deep learning Techniques. Giró-i-Nieto X. 2015.  (1.57 MB)
Pan J, McGuinness K, Sayrol E, O'Connor N, Giró-i-Nieto X. Shallow and Deep Convolutional Networks for Saliency Prediction. In IEEE Conference on Computer Vision and Pattern Recognition, CVPR. Las Vegas, NV, USA: Computer Vision Foundation / IEEE; 2016.  (466.13 KB)
Panizo E. Classification techniques for Alzheimer’s disease early diagnosis. Vilaplana V. 2015.  (5.86 MB)
Pardàs M. Object-base image coding. Vistas in astronomy. 1997;41:455–461.
Pardàs M, Bonafonte A. Work in progress - Cooperative and competitive projects for engaging students in advanced ICT subjects. In 41st Annual Frontiers in Education Conference. 2011. pp. 1–3.
Pardàs M, Sayrol E. A new approach to active contours for tracking. In IEEE International Conference on Image Processing. 2000.
Pardàs M, Salembier P. Joint region and motion estimation with morphological tools. In International Symposium on Mathematical Morphology, ISMM 1994. Fontainebleau, France; 1994.
Pardàs M, Sayrol E. Motion estimation based tracking of active contours. Pattern recognition letters. 2001;22:1447–1456.
Pardàs M, Salembier P. Time-recursive segmentation of image sequences. In European Signal Processing Conference, EUSIPCO-94. Edinburgh, UK; 1994. pp. 18–21.  (806.06 KB)
Pardàs M. Relative depth estimation and segmentation in monocular sequences. In 1997 PICTURE CODING SYMPOSIUM. 1997. pp. 367–372.
Pardàs M, Anglada D, Espina M, Marques F, Salembier P. Stromal tissue segmentation in Ki67 histology images based on cytokeratin-19 stain translation. JOURNAL OF MEDICAL IMAGING. 2023;10(3).  (13.78 MB)
Pardàs M, Salembier P, Torres L. 3D morphological segmentation or image sequence processing. In IEEE Winter Workshop on Nonlinear Signal Processing. Tampere, Finland; 1993. pp. 31–36.

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