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Pardàs M, Bonafonte A. Facial animation parameters extraction and expression recognition using Hidden Markov Models. Signal processing: image communication. 2002;:675–688.
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. Time-recursive segmentation of image sequences. In European Signal Processing Conference, EUSIPCO-94. Edinburgh, UK; 1994. pp. 18–21.  (806.06 KB)
Panizo E. Classification techniques for Alzheimer’s disease early diagnosis. Vilaplana V. 2015.  (5.86 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, 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)
Pan J. Visual Saliency Prediction using Deep learning Techniques. Giró-i-Nieto X. 2015.  (1.57 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)
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. Hierarchical Video Representation with Trajectory Binary Partition Tree. In Computer Vision and Pattern Recognition (CVPR). Portland, Oregon; 2013.  (4.69 MB)
Palou G, Salembier P. Monocular Depth Ordering Using Occlusion Cues. Barcelona: Technical University of Catalonia; 2011 .
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. 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)
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. Depth order estimation for video frames using motion occlusions. IET Computer Vision. 2014;8(2):152-160.  (910.25 KB)
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. 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. 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)
Pachón-García C, Hernandez C, Delicado P, Vilaplana V. SurvLIMEpy: A Python package implementing SurvLIME. Expert Systems With Applications. 2024;237, Part C.

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