Diferencia entre revisiones de «Enlaces de interes»
De Grupo de Inteligencia Computacional (GIC)
(→datos) |
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| (No se muestran 66 ediciones intermedias del mismo usuario) | |||
| Línea 1: | Línea 1: | ||
===quantum sensing=== | |||
* tutorial [https://learn.keysight.com/quantum-sensing/lesson-1-introduction-21] | |||
* video quantum sensing perspectives [https://www.youtube.com/live/sqACWPrbEd0?feature=share] | |||
===proyectos interesantes === | |||
http://www.midasproject.eu | |||
https://ebrains.eu | |||
https://entimement.dibris.unige.it | |||
https://eyewear-computing.org/EPIC_CVPR20/ | |||
toxtrac https://www.youtube.com/watch?v=RaVTsQ1JwfM | |||
precision medicine & cancer [https://precisionmedicinemaastricht.eu/] | |||
deep fake videos [https://wwwhatsnew.com/2021/01/02/algunas-opciones-para-crear-deepfakes-en-video/] | |||
https://www.philhumans.eu/ | |||
https://aerial-core.eu/ | |||
https://www.robotics4eu.eu/ | |||
=== EEG y BCI=== | |||
https://neuroinformatics.gr | |||
https://team.inria.fr/hybrid/ | |||
http://www.mindbigdata.com/opendb/ | |||
=== Challenges === | === Challenges === | ||
* segmentacion de ictus multimodal MRI [http://www.isles-challenge.org] | * segmentacion de ictus multimodal MRI [http://www.isles-challenge.org] | ||
* retinopatia diabetica [http://www.kaggle.com/c/diabetic-retinopathy-detection] | * retinopatia diabetica [http://www.kaggle.com/c/diabetic-retinopathy-detection] | ||
* http://av-test-challenge.org/index.html# | |||
=== | ===deep learning generals === | ||
* | * stylegan [https://nvlabs.github.io/stylegan2/versions.html] | ||
* | * https://deepmind.com/blog/article/using-jax-to-accelerate-our-research | ||
* deep unsupervised learning [https://sites.google.com/view/berkeley-cs294-158-sp20/home] | |||
* ucdavis 2018 winter [https://web.cs.ucdavis.edu/~yjlee/teaching/ecs289g-winter2018/] | |||
* deep learning book [http://www.deeplearningbook.org] | |||
*curso de standford [http://cs231n.stanford.edu] | *curso de standford [http://cs231n.stanford.edu] [https://cs230.stanford.edu/] [http://cs231n.stanford.edu/2021/] | ||
* Illinois [http://slazebni.cs.illinois.edu/spring17/] | * Illinois [http://slazebni.cs.illinois.edu/spring17/] | ||
| Línea 19: | Línea 61: | ||
*Representation Learning on Networks [http://snap.stanford.edu/proj/embeddings-www/] | *Representation Learning on Networks [http://snap.stanford.edu/proj/embeddings-www/] | ||
* curso ML en el mit de 2013 [http://people.csail.mit.edu/dsontag/courses/ml13/slides/] | |||
* implementación Matlab de GCN [https://github.com/jiechenjiechen/FastGCN-matlab] | |||
* serie de charlas sobre AI [https://www.youtube.com/channel/UCZgLH0CsLNMUCTLQRqry4qA] | |||
=== reinforcement learning=== | |||
https://cs.uwaterloo.ca/~ppoupart/ICML-07-tutorial-slides/ | |||
http://web.stanford.edu/class/cs234/CS234Win2019/index.html | |||
=== dialog systems === | === dialog systems === | ||
| Línea 28: | Línea 82: | ||
===Time series === | ===Time series === | ||
* Forecasting: Principles and Practice [https://otexts.com/fpp2/] | |||
* clases de time series en Berkeley 2010 [https://www.stat.berkeley.edu/~bartlett/courses/153-fall2010/] | * clases de time series en Berkeley 2010 [https://www.stat.berkeley.edu/~bartlett/courses/153-fall2010/] | ||
* tutorial con keras [https://machinelearningmastery.com/time-series-prediction-lstm-recurrent-neural-networks-python-keras/] | * tutorial con keras [https://machinelearningmastery.com/time-series-prediction-lstm-recurrent-neural-networks-python-keras/] | ||
* toolbox para extraer características musicales [https://www.jyu.fi/hytk/fi/laitokset/mutku/en/research/materials/mirtoolbox] | |||
=== lenguaje natural === | === lenguaje natural === | ||
* standford 2018 [https://web.stanford.edu/class/cs124/] | * standford 2018 [https://web.stanford.edu/class/cs124/] | ||
* https://github.com/neubig/nlptutorial | |||
* tutorial en python [https://www.youtube.com/watch?v=xvqsFTUsOmc] | |||
===Redes sociales=== | ===Redes sociales=== | ||
* bases de datos del Max Plank [http://socialnetworks.mpi-sws.org/datasets.html] | |||
* bases de datos de large networks [http://snap.stanford.edu/data/#signnets] | * bases de datos de large networks [http://snap.stanford.edu/data/#signnets] | ||
| Línea 48: | Línea 110: | ||
=== Enlaces de visión por computador y proceso de imagen=== | === Enlaces de visión por computador y proceso de imagen=== | ||
* machine learning depth computation [https://mannequin-depth.github.io/] | * animal tracking papers [https://github.com/anl13/animal_papers] | ||
* deeplabcut tutorial workshop [https://github.com/DeepLabCut/DeepLabCut-Workshop-Materials] y deepPoseKit [https://github.com/jgraving/DeepPoseKit] | |||
* base de datos de crowd analysis [http://www.cse.psu.edu/~rtc12/software.html] | |||
* facial expresión at google. [https://research.google/tools/datasets/google-facial-expression/] | |||
* reconocimiento de las. pose 3D de la mano [https://paperswithcode.com/task/3d-hand-pose-estimation] papeles con código | |||
* Action Recognition Data Set [https://www.crcv.ucf.edu/data/UCF101.php] | |||
* videos anotados de detección de vehículos [http://cmp.felk.cvut.cz/data/motorway/] y segmentación de carreteras y carriles [http://www.cvlibs.net/datasets/kitti/eval_road.php] | |||
* common objects in context [http://cocodataset.org/#home] api [https://github.com/cocodataset/cocoapi] | |||
* oxford RobotCar data [https://ori.ox.ac.uk/oxford-radar-robotcar-dataset/] | |||
* machine learning depth from video computation from mannequin challenge [https://mannequin-depth.github.io/] | |||
* canal youtube de la CVF [https://www.youtube.com/channel/UC0n76gicaarsN_Y9YShWwhw/videos?disable_polymer=1] | * canal youtube de la CVF [https://www.youtube.com/channel/UC0n76gicaarsN_Y9YShWwhw/videos?disable_polymer=1] | ||
| Línea 60: | Línea 140: | ||
* calibración en MATLAB [http://www.vision.caltech.edu/bouguetj/calib_doc/] | * calibración en MATLAB [http://www.vision.caltech.edu/bouguetj/calib_doc/] | ||
* CVonline [http://homepages.inf.ed.ac.uk/rbf/CVonline/] | * CVonline [http://homepages.inf.ed.ac.uk/rbf/CVonline/] | ||
* bases de datos de vision por computador online [http://homepages.inf.ed.ac.uk/rbf/CVonline/Imagedbase.htm] | * bases de datos de vision por computador online [http://homepages.inf.ed.ac.uk/rbf/CVonline/Imagedbase.htm] | ||
| Línea 119: | Línea 194: | ||
* Revista electrónica de visión por computador mantenida por el CVC de la UAB: http://elcvia.cvc.uab.es | * Revista electrónica de visión por computador mantenida por el CVC de la UAB: http://elcvia.cvc.uab.es | ||
* Una wiki sobre computer vision http://inperc.com/wiki/index.php?title=Main_Page | * Una wiki sobre computer vision http://inperc.com/wiki/index.php?title=Main_Page | ||
| Línea 131: | Línea 205: | ||
* document image binarization 2018 [https://vc.ee.duth.gr/h-dibco2018/] | * document image binarization 2018 [https://vc.ee.duth.gr/h-dibco2018/] | ||
====datos==== | |||
* datos para tracking [http://got-10k.aitestunion.com] | |||
* imagenes hiperspectrales de TU Berlin [https://hyspecnet.rsim.berlin/] | |||
* roboflow top datasets for manufacturing computer vision [https://universe.roboflow.com/browse/manufacturing] | |||
* Image Database At The Johns Hopkins CIS: [http://www.cis.jhu.edu/data.sets/index.html] | |||
* https://homepages.inf.ed.ac.uk/rbf/SURGICALTOOLS/ | |||
====cursos ==== | |||
* curso de tracking animals [https://guillermohidalgogadea.com/teaching/tracking-animal-behavior/] | |||
* pose detection en CMU [https://www.cs.cmu.edu/~yaser/] | |||
* cursos de vision por computador [http://www.cse.psu.edu/~rtc12/CSE486/], [http://www.cs.cmu.edu/~16385/] [https://cs.brown.edu/courses/csci1430/] [https://www.cs.rutgers.edu/~elgammal/classes/cs534/cs534.html] [https://courses.cs.washington.edu/courses/cse576/08sp/] [http://www-inst.eecs.berkeley.edu/~cs280/sp15/index.html] [https://canvas.instructure.com/courses/904706/pages/lecture-slides] [http://cs.brown.edu/courses/csci1430/2020_Spring/index.html] [https://filebox.ece.vt.edu/~jbhuang/teaching/ece5554-4554/fa16/lectures.html] | |||
* cursos de image processing [http://www.ctr.maths.lu.se/course/imagean/2013/] [https://www.cs.rutgers.edu/~elgammal/cs334.htm] [http://graphics.cs.cmu.edu/courses/15-463/] | |||
* Computer Vision: Algorithms and Applications, by Richard Szelirki. [http://szeliski.org/Book/] | |||
* Stanford Convolutional Neural Networks for Visual Recognition: [http://cs231n.stanford.edu/] | |||
* Washington University Computer Vision: [https://courses.cs.washington.edu/courses/cse455/22sp/] | |||
* New York University Computer Vision: [https://cs.nyu.edu/~fergus/teaching/vision/index.html] | |||
===remote sensing=== | ===remote sensing=== | ||
| Línea 137: | Línea 237: | ||
* target detection site hyper spectral images [http://dirsapps.cis.rit.edu/blindtest/] | * target detection site hyper spectral images [http://dirsapps.cis.rit.edu/blindtest/] | ||
* repositorios de imágenes de satélite [https://github.com/chrieke/awesome-satellite-imagery-datasets] | |||
=== OpenCV=== | === OpenCV=== | ||
| Línea 143: | Línea 245: | ||
=== Proceso de señal e imagen médica === | === Proceso de señal e imagen médica === | ||
* functional connectivity toolbox CONN [https://web.conn-toolbox.org/home] | |||
* mobile brain and imaging [https://mobi-award.com/#research] | |||
* [http://sccn.ucsd.edu/wiki/EEGLAB_2011_Aspet EEGLAB 2011 Aspet] | * [http://sccn.ucsd.edu/wiki/EEGLAB_2011_Aspet EEGLAB 2011 Aspet] | ||
| Línea 194: | Línea 300: | ||
=== bases de datos de imagen medica === | === bases de datos de imagen medica === | ||
* http://medicaldecathlon.com/ | |||
* Image Sciences Institute Utrech Univ. [http://www.isi.uu.nl/Research/Databases/] | * Image Sciences Institute Utrech Univ. [http://www.isi.uu.nl/Research/Databases/] | ||
| Línea 220: | Línea 328: | ||
===Enlaces de proveedores de material de visión === | ===Enlaces de proveedores de material de visión === | ||
* bases de datos de imágenes industriales de MVTEC [https://www.mvtec.com/company/research/datasets/] | |||
* lidar barato [https://www.indiegogo.com/projects/navipack-lidar-navigation-module-reinvented#/] | * lidar barato [https://www.indiegogo.com/projects/navipack-lidar-navigation-module-reinvented#/] | ||
| Línea 240: | Línea 350: | ||
=== Enlaces de robótica === | === Enlaces de robótica === | ||
* https://ai2thor.allenai.org/ | |||
* simulador de drones [https://microsoft.github.io/AirSim/] | |||
* curso de navegacion [http://www.ee.nmt.edu/~elosery/spring_2016/ee570/lectures.php] | * curso de navegacion [http://www.ee.nmt.edu/~elosery/spring_2016/ee570/lectures.php] | ||
| Línea 293: | Línea 407: | ||
* Ejemplos de Estilos en Bibtex (I) http://www.cs.stir.ac.uk/~kjt/software/latex/showbst.html | * Ejemplos de Estilos en Bibtex (I) http://www.cs.stir.ac.uk/~kjt/software/latex/showbst.html | ||
* Ejemplos de Estilos en Bibtex (II) http://amath.colorado.edu/documentation/LaTeX/reference/faq/bibstyles.pdf | * Ejemplos de Estilos en Bibtex (II) http://amath.colorado.edu/documentation/LaTeX/reference/faq/bibstyles.pdf | ||
=== estilos beamer === | |||
https://mpetroff.net/files/beamer-theme-matrix/ | |||
https://deic.uab.es/~iblanes/beamer_gallery/individual/Dresden-seahorse-default.html | |||
=== enlaces de recursos en R === | |||
* histogramas [https://homepage.divms.uiowa.edu/~luke/classes/STAT4580/histdens.html#superimposing-a-density] | |||
* top 50 ggplot visualizations [http://r-statistics.co/Top50-Ggplot2-Visualizations-MasterList-R-Code.html] | |||
===Enlances de Computational Intelligence === | ===Enlances de Computational Intelligence === | ||
* Matlab Toolbox for Dimensionality Reduction [https://lvdmaaten.github.io/drtoolbox/#usage] | |||
* David Wolfe Corne [http://www.macs.hw.ac.uk/~dwcorne/] | * David Wolfe Corne [http://www.macs.hw.ac.uk/~dwcorne/] | ||
* [http://videolectures.net/bootcamp2010_murray_iml/ Introduction to machine learning video by Iain Murray] | * [http://videolectures.net/bootcamp2010_murray_iml/ Introduction to machine learning video by Iain Murray] | ||
| Línea 302: | Línea 429: | ||
* toolbox de nonlinear dimensional reduction [https://lvdmaaten.github.io/drtoolbox/ ] | * toolbox de nonlinear dimensional reduction [https://lvdmaaten.github.io/drtoolbox/ ] | ||
* ICALAB dela Universida de RIken, Japon [http://www.bsp.brain.riken.jp/ICALAB/] | * ICALAB dela Universida de RIken, Japon [http://www.bsp.brain.riken.jp/ICALAB/] | ||
* fastICA del grupo de Kohonen [http://www.cis.hut.fi/projects/ica/fastica/] | * fastICA del grupo de Kohonen [http://www.cis.hut.fi/projects/ica/fastica/] | ||
* LIBSVM [http://www.csie.ntu.edu.tw/~cjlin/libsvm/] | * LIBSVM [http://www.csie.ntu.edu.tw/~cjlin/libsvm/] | ||
Revisión del 20:07 21 nov 2023
quantum sensing
- tutorial [1]
- video quantum sensing perspectives [2]
proyectos interesantes
https://entimement.dibris.unige.it
https://eyewear-computing.org/EPIC_CVPR20/
toxtrac https://www.youtube.com/watch?v=RaVTsQ1JwfM
precision medicine & cancer [3]
deep fake videos [4]
EEG y BCI
http://www.mindbigdata.com/opendb/
Challenges
- segmentacion de ictus multimodal MRI [5]
- retinopatia diabetica [6]
- http://av-test-challenge.org/index.html#
deep learning generals
- stylegan [7]
- deep unsupervised learning [8]
- ucdavis 2018 winter [9]
- deep learning book [10]
- Illinois [14]
- berkeley [15]
- Representation Learning on Networks [16]
- curso ML en el mit de 2013 [17]
- implementación Matlab de GCN [18]
- serie de charlas sobre AI [19]
reinforcement learning
https://cs.uwaterloo.ca/~ppoupart/ICML-07-tutorial-slides/
http://web.stanford.edu/class/cs234/CS234Win2019/index.html
dialog systems
- curso stanford 2017 [20]
- curso washington 2017 [21]
Time series
- tutorial con keras [24]
- toolbox para extraer características musicales [25]
lenguaje natural
- standford 2018 [26]
- https://github.com/neubig/nlptutorial
- tutorial en python [27]
Redes sociales
- bases de datos del Max Plank [28]
- bases de datos de large networks [29]
- proyecto colaborativo de demostracion de teoremas [30]
- software de modelado de sistemas de colas en Java [31]
- sentiment analysis [32]
Enlaces de visión por computador y proceso de imagen
- animal tracking papers [33]
- base de datos de crowd analysis [36]
- facial expresión at google. [37]
- reconocimiento de las. pose 3D de la mano [38] papeles con código
- Action Recognition Data Set [39]
- oxford RobotCar data [44]
- machine learning depth from video computation from mannequin challenge [45]
- canal youtube de la CVF [46]
- color en python [47]
- codigos de Jun LI [48]
- CVIP tools [49]
- calibración en MATLAB [50]
- CVonline [51]
- bases de datos de vision por computador online [52]
- una implementación de redes convolucionales para retina [53]
- bases de datos del Max Plank Institute for Informatics [54]
- caltech 101 dataset [55]
- proyectos para asignatura de vision por computador [56]
- software de Antonio Plaza para imagenes hiperespectrales [57]
- bristol hyperspectral images database
- bases de datos de video online para validación [58]
- slides del libro Similarity Search [59]
- portal de Image Fusion [60]
- base de datos de expresiones Cohn-Kanade AU-Coded Facial Expression Database [61]
- referencia a multiples bases de datos de imagenes para experimentacion [62]
- face detection using SVM [63], Matlab & C++ implementations
- IIM Virtual Laboratory de la ESA [64]
- Computational Geometry Algorithms Library (CGAL) [65]
- On line compendium of Computer Vision [66]
- Imagenes para testar color constancy http://www.cs.sfu.ca/~colour/data/colour_constancy_synthetic_test_data/index.html
- Mathematical Biosciencies Institute at the Ohio State University : http://mbi.osu.edu/
- Test comparativo de algoritmos de visión estéreo: http://vision.middlebury.edu/stereo/
- Sobre anotación de video: NIST tiene una serie de conferencias y datos públicos: TREC Video Retrieval Evaluation [67]
- Base de datos de videos para experimentación http://www.open-video.org/
- Amsterdam Library of Object Images (ALOI) [68]
- Grupo de visión de la universidad de Zurich: http://www.vision.ee.ethz.ch/
- Revista electrónica de visión por computador mantenida por el CVC de la UAB: http://elcvia.cvc.uab.es
- Una wiki sobre computer vision http://inperc.com/wiki/index.php?title=Main_Page
- The Matlab Toolbox for Pattern Recognition [69]
- proceso de imagenes de patologia celular [72]
- document image binarization 2018 [73]
datos
- datos para tracking [74]
- imagenes hiperspectrales de TU Berlin [75]
- roboflow top datasets for manufacturing computer vision [76]
- Image Database At The Johns Hopkins CIS: [77]
cursos
- curso de tracking animals [78]
- pose detection en CMU [79]
- Computer Vision: Algorithms and Applications, by Richard Szelirki. [92]
- Stanford Convolutional Neural Networks for Visual Recognition: [93]
- Washington University Computer Vision: [94]
- New York University Computer Vision: [95]
remote sensing
- int. school on LiDAR [96]
- target detection site hyper spectral images [97]
- repositorios de imágenes de satélite [98]
OpenCV
Proceso de señal e imagen médica
- functional connectivity toolbox CONN [101]
- mobile brain and imaging [102]
- Curso HyperVision 2009, Boston, traspas + video + audio [103]
- Cursos de Procesamiento de Imagen Médica: Opencourseware (MIT)
- FMRIB Software Library FSL [106]
- Statistical Parametric Mapping SPM [108], versión 8 [109], información dentro de nuestro groupware [110]
- Toolbox de ICA que se integra en SPM [111]
- International Consortium for Brain Mapping (ICBM)[112]
- BrainMap [113]
- Princeton Multi Voxel Pattern Analysis [114]
- MedicalStudio: un paquete que integra VTK, GTK, DCMTK e ITK que está en preparación [115] - Licencia GPL.
- 3DSlicer [116] - BSD-style license (free)
- MITK [117] - BSD-style license (free)
- VolView [118] - Privativo
- MeVisLab [119] - El SDK es privativo, paquete básico gratis para uso no comercial.
- Data Analysis and visualization software [120] - BSD-style license (free)
- BrainSuite2 - Skull Stripping Algorithm (A.K.A BSE) - for Windows - Licencia no libre [121]
- GIFT una toolbox Matlab para la aplicación de ICA a fMRI [122]
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas [123]
bases de datos de imagen medica
- Image Sciences Institute Utrech Univ. [124]
- Base de datos de Ictus con imagenes MRI [125]
- Open fMRI data [126]
- colección MIDAS de imágenes de resonancia incluyendo imágenes de lesiones [127]
- cancer imaging archive [128]
recursos de human brain mapping
Van Essen Lab cartografia cerebral
large scale model of the functioning brain
clinical predictions from structural brain MRI
Enlaces de proveedores de material de visión
- bases de datos de imágenes industriales de MVTEC [129]
- lidar barato [130]
- ¿soluciones hiperespectrales? [131]
- Camaras hiperespectrales SPCIM [132]
- Material para visión por computador: http://www.vhtm.com
- The Imaging Source: http://www.theimagingsource.com
- Edmund Optics: http://www.edmundoptics.co.uk
- Cámara wireless Linksys [133]
- Cámaras hiperespectrales y software [134]
- cámaras estereo y esféricas [135]
Enlaces de robótica
- simulador de drones [136]
- curso de navegacion [137]
- motion planning tutorial [138]
- robotic operating system ROS [139]
- centro de excelencia de cognition for technical systems, munich [142]
- summer school in Botchum [143]
- Desarrollo de agentes en Java: JADE http://jade.tilab.com/
- Red europea de robótica EURON: http://www.euron.org/
- Simulador 3D de robots en Java: http://simbad.sourceforge.net/
- Simulador Gazebo de robots 3D: Linux & Mac --- http://playerstage.sourceforge.net/gazebo/gazebo.html
- Simulador del Aibo [144]
- Netlogo simulador Java de sistemas multiagente http://ccl.northwestern.edu/netlogo/
- repositorio de articulos de SLAM [145]
Enlaces de proveedores de material robótica
- COMPLUBOT [146]
- Robótica fácil: superRobotica, ¡¡atención al SR1!! http://www.superrobotica.com/
- Robots Videre [153]
- Ro-Botica: [154]
- Listado de tiendas de Robótica y Domótica: [155]
- Listado de fabricantes y plataformas robóticas para desarrollo y ocio: [156]
Enlaces de recursos latex
- Lista de paquetes latex http://tex.loria.fr/english/packages.html
- Ejemplos de Estilos en Bibtex (I) http://www.cs.stir.ac.uk/~kjt/software/latex/showbst.html
- Ejemplos de Estilos en Bibtex (II) http://amath.colorado.edu/documentation/LaTeX/reference/faq/bibstyles.pdf
estilos beamer
https://mpetroff.net/files/beamer-theme-matrix/
https://deic.uab.es/~iblanes/beamer_gallery/individual/Dresden-seahorse-default.html
enlaces de recursos en R
Enlances de Computational Intelligence
- Matlab Toolbox for Dimensionality Reduction [159]
- David Wolfe Corne [160]
- Introduction to machine learning video by Iain Murray
- una alternative alemana al weka ?? [161]
- time series en r [162] [163]
- toolbox de nonlinear dimensional reduction [164]
- ICALAB dela Universida de RIken, Japon [165]
- fastICA del grupo de Kohonen [166]
- LIBSVM [167]
Indices de impacto
- Eigenfactor: índices de factores de impacto de revistas científicas [168]
- artnetminer [169]
Convocatorias de proyectos, becas y premios
- calls - clinical decision support [170]
- pagina del vicerrectorado de investigación con lista de convocatorias [171]
- becas predoctorales del gobierno vasco 2011 [172]
- Convocatorias europeas sobre informática y comunicaciones texto
- Convocatoria de proyectos del Ministerio de Ciencia e Innovación [173]
- Plan de Ciencia, Tecnología e Innovación 2001-2004. Departamento de Industria, Comercio y Turismo. Gobierno Vasco. [174]
- Plan de Ciencia, Tecnología e Innovación 2010. Departamento de Industria, Comercio y Turismo. Gobierno Vasco. [175]
redes europeas
- innovative training networks --- 13 enero 2015 [176]
- Synergy [177]
- summer school at Botchum [178]
Cursos de formación
Medical Imaging
- Maastricht Brain Imaging Center Courses - Next on: fMRI Workshop 2009 (February 17-20, 2009)
- Martinos Center Courses - Next on: Two-Week Multi-Modality Short Course (June 1-12, 2009)
- SPM Course (this year's is fully booked May 7-9, 2009)
- SPM Course 2009 at Zurich. (11-13 February, 2009)
