Diferencia entre revisiones de «Enlaces de interes»

De Grupo de Inteligencia Computacional (GIC)
(No se muestran 73 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]


=== Scientific computing general ===
* https://deepmind.com/blog/article/using-jax-to-accelerate-our-research


* Introduccion a scientific computing [http://www.cse.illinois.edu/heath/scicomp/notes/index.html]
* deep unsupervised learning [https://sites.google.com/view/berkeley-cs294-158-sp20/home]


* diagramas de gantt en python �[http://thetimelineproj.sourceforge.net/installing.html]
* ucdavis 2018 winter [https://web.cs.ucdavis.edu/~yjlee/teaching/ecs289g-winter2018/]


===deep learning generals ===
* deep learning book [http://www.deeplearningbook.org]
 
*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/]


* berkeley [http://rail.eecs.berkeley.edu/deeprlcourse/]
* berkeley [http://rail.eecs.berkeley.edu/deeprlcourse/]
*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 24: 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 43: Línea 109:


=== Enlaces de visión por computador y proceso de imagen===
=== Enlaces de visión por computador y proceso de imagen===
* 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]


* color en python [https://zenodo.org/record/2647615#.XMgWupMzaV4]
* color en python [https://zenodo.org/record/2647615#.XMgWupMzaV4]
Línea 52: Línea 140:
* calibración en MATLAB [http://www.vision.caltech.edu/bouguetj/calib_doc/]
* calibración en MATLAB [http://www.vision.caltech.edu/bouguetj/calib_doc/]


* 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]


* 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/]


* CVonline [http://homepages.inf.ed.ac.uk/rbf/CVonline/]
* CVonline [http://homepages.inf.ed.ac.uk/rbf/CVonline/]


* Computer Vision: Algorithms and Applications, by Richard Szelirki. [http://szeliski.org/Book/]


* 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 111: 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


* Image Database At The Johns Hopkins CIS: [http://www.cis.jhu.edu/data.sets/index.html]


* 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 120: Línea 202:


* proceso de imagenes de patologia celular [https://github.com/qupath/qupath/blob/master/README.md]
* proceso de imagenes de patologia celular [https://github.com/qupath/qupath/blob/master/README.md]
* 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===
* int. school on LiDAR [http://home.iitk.ac.in/~blohani/LiDARSchool2008/downloads.html]


* target detection site hyper spectral images [http://dirsapps.cis.rit.edu/blindtest/]
* target detection site hyper spectral images [http://dirsapps.cis.rit.edu/blindtest/]


* document image binarization 2018 [https://vc.ee.duth.gr/h-dibco2018/]
* repositorios de imágenes de satélite [https://github.com/chrieke/awesome-satellite-imagery-datasets]


=== OpenCV===
=== OpenCV===
Línea 130: 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 181: 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 207: 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#/]


* ¿soluciones hiperespectrales? [http://www.spectir.com/]
* ¿soluciones hiperespectrales? [http://www.spectir.com/]
Línea 225: 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 278: 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]
* una alternative alemana al weka ?? [http://www.knime.org/]
* una alternative alemana al weka ?? [http://www.knime.org/]
* time series en r [http://www.stat.pitt.edu/stoffer/tsa4/R_toot.htm] [https://www.statmethods.net/advstats/timeseries.html]
* time series en r [http://www.stat.pitt.edu/stoffer/tsa4/R_toot.htm] [https://www.statmethods.net/advstats/timeseries.html]
====ICA====
 
* 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/]
====SVM====


* 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

  • video quantum sensing perspectives [2]

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 [3]


deep fake videos [4]

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

deep learning generals

  • deep unsupervised learning [8]
  • ucdavis 2018 winter [9]
  • deep learning book [10]
  • 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

  • Forecasting: Principles and Practice [22]
  • clases de time series en Berkeley 2010 [23]
  • tutorial con keras [24]
  • toolbox para extraer características musicales [25]

lenguaje natural

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]
  • deeplabcut tutorial workshop [34] y deepPoseKit [35]
  • 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]
  • videos anotados de detección de vehículos [40] y segmentación de carreteras y carriles [41]
  • 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]
  • calibración en MATLAB [50]



  • 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]
  • 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]
  • Sobre anotación de video: NIST tiene una serie de conferencias y datos públicos: TREC Video Retrieval Evaluation [67]
  • Amsterdam Library of Object Images (ALOI) [68]


  • The Matlab Toolbox for Pattern Recognition [69]
  • pagina de Scott Umabaugh, Illonois [70] con recopilacion de articulos sobre retina [71]
  • 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

  • tutoriales Python y OpenCV [99] más reciente (2014) [100]

Proceso de señal e imagen médica

  • functional connectivity toolbox CONN [101]
  • mobile brain and imaging [102]
  • Curso HyperVision 2009, Boston, traspas + video + audio [103]
  • Training Course in fMRI 2008 (University of Michigan's Functional MRI Laboratory )[104]) : [105]
  • FMRIB Software Library FSL [106]
  • Librería ITK de software para imagen médica: [107] y su filosofía de software libre itk fre
  • 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]
  • 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

the virtual brain

human connectome project

1000 functional connectomes

Van Essen Lab cartografia cerebral

niconnect

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]
  • ¿soluciones hiperespectrales? [131]
  • Camaras hiperespectrales SPCIM [132]
  • 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]
  • enlace de ROS y el SDK de airdrone [140]
    • compilando en Ubuntu [141]
  • centro de excelencia de cognition for technical systems, munich [142]
  • summer school in Botchum [143]
  • repositorio de articulos de SLAM [145]

Enlaces de proveedores de material robótica

  • Listado de tiendas de Robótica y Domótica: [155]
  • Listado de fabricantes y plataformas robóticas para desarrollo y ocio: [156]

Enlaces de recursos latex

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 [157]
  • top 50 ggplot visualizations [158]

Enlances de Computational Intelligence

  • toolbox de nonlinear dimensional reduction [164]
  • ICALAB dela Universida de RIken, Japon [165]
  • fastICA del grupo de Kohonen [166]

Indices de impacto

  • Eigenfactor: índices de factores de impacto de revistas científicas [168]

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
  • 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]
    • summer school at Botchum [178]

Cursos de formación

Medical Imaging

  • SPM Course (this year's is fully booked May 7-9, 2009)

Mathematics

Cosas obsoletas de datos y direcciones de interés

Obtenido de «http://ehu.eus/ccwintco/index.php?title=Enlaces_de_interes&oldid=20242»