2018 - Fellow of the American Academy of Arts and Sciences
2013 - SIAM Fellow For contributions to both theory and practice in the fields of image processing and computer vision.
His primary scientific interests are in Artificial intelligence, Computer vision, Image processing, Pattern recognition and Image segmentation. Artificial intelligence is a component of his Inpainting, Pixel, Segmentation, K-SVD and Image restoration studies. The study incorporates disciplines such as Tractography, Temporal resolution and Pattern recognition in addition to Computer vision.
The various areas that Guillermo Sapiro examines in his Image processing study include Computational complexity theory, Algorithm and Grayscale. In his study, Regularization and Cluster analysis is strongly linked to Linear subspace, which falls under the umbrella field of Pattern recognition. His studies deal with areas such as Object detection and Geodesic as well as Image segmentation.
Guillermo Sapiro focuses on Artificial intelligence, Computer vision, Pattern recognition, Algorithm and Image processing. Guillermo Sapiro frequently studies issues relating to Machine learning and Artificial intelligence. His Pattern recognition research is multidisciplinary, incorporating perspectives in Contextual image classification, Sparse matrix and Image restoration.
His Algorithm research is multidisciplinary, relying on both Convolutional neural network, Artificial neural network, Representation, Mathematical optimization and Geodesic. His Image processing study frequently draws connections between adjacent fields such as Partial differential equation. His work is dedicated to discovering how Anisotropic diffusion, Mathematical analysis are connected with Affine transformation and other disciplines.
His main research concerns Artificial intelligence, Algorithm, Pattern recognition, Machine learning and Artificial neural network. Many of his studies on Artificial intelligence apply to Computer vision as well. His Computer vision study combines topics from a wide range of disciplines, such as Autism and Autism spectrum disorder.
His biological study spans a wide range of topics, including Contextual image classification, Linear combination, Convolutional neural network and Filter. His Pattern recognition study combines topics in areas such as Probabilistic logic, Diffusion MRI and Code. His study looks at the relationship between Artificial neural network and fields such as Embedding, as well as how they intersect with chemical problems.
The scientist’s investigation covers issues in Artificial intelligence, Algorithm, Artificial neural network, Autism and Computer vision. His Artificial intelligence research includes themes of Machine learning and Pattern recognition. His work deals with themes such as Ground truth and Probabilistic logic, which intersect with Pattern recognition.
His Algorithm research incorporates themes from Data set, Convolutional neural network and Robustness. Guillermo Sapiro has included themes like Training set, Inverse problem, Matrix norm, Contextual image classification and Mathematical optimization in his Artificial neural network study. His work carried out in the field of Computer vision brings together such families of science as Affect and Adaptive optics.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
Geodesic active contours
V. Caselles;R. Kimmel;G. Sapiro.
international conference on computer vision (1995)
Image inpainting
Marcelo Bertalmio;Guillermo Sapiro;Vincent Caselles;Coloma Ballester.
international conference on computer graphics and interactive techniques (2000)
Online Learning for Matrix Factorization and Sparse Coding
Julien Mairal;Francis Bach;Jean Ponce;Guillermo Sapiro.
Journal of Machine Learning Research (2010)
Online dictionary learning for sparse coding
Julien Mairal;Francis Bach;Jean Ponce;Guillermo Sapiro.
international conference on machine learning (2009)
A collaborative framework for 3D alignment and classification of heterogeneous subvolumes in cryo-electron tomography
Oleg Kuybeda;Gabriel A. Frank;Alberto Bartesaghi;Mario Borgnia.
Journal of Structural Biology (2013)
The LOCO-I lossless image compression algorithm: principles and standardization into JPEG-LS
M.J. Weinberger;G. Seroussi;G. Sapiro.
IEEE Transactions on Image Processing (2000)
Sparse Representation for Computer Vision and Pattern Recognition
John Wright;Yi Ma;Julien Mairal;Guillermo Sapiro.
Proceedings of the IEEE (2010)
Sparse Representation for Color Image Restoration
J. Mairal;M. Elad;G. Sapiro.
IEEE Transactions on Image Processing (2008)
Robust anisotropic diffusion
M.J. Black;G. Sapiro;D.H. Marimont;D. Heeger.
IEEE Transactions on Image Processing (1998)
Non-local sparse models for image restoration
Julien Mairal;Francis Bach;Jean Ponce;Guillermo Sapiro.
international conference on computer vision (2009)
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