.. image:: pyeco.png
:height: 20
:alt: Economie
:target: http://www.xavierdupre.fr/app/ensae_teaching_cs/helpsphinx/td_2a_notions.html#pour-un-profil-plutot-economiste
.. image:: pystat.png
:height: 20
:alt: Statistique
:target: http://www.xavierdupre.fr/app/ensae_teaching_cs/helpsphinx/td_2a_notions.html#pour-un-profil-plutot-data-scientist
Classification d'images
+++++++++++++++++++++++
(*à venir*)
*Lectures*
* `VGG Convolutional Neural Networks Practical `_
* `Image-to-Image Translation with Conditional Adversarial Networks `_,
`Image to Image demo `_
* `Image-to-Image Translation with Conditional Adversarial Networks `_
* `How to Train a GAN? Tips and tricks to make GANs work `_
* `Towards Principled Methods for Training Generative Adversarial Networks `_
* `Instance Noise: A trick for stabilising GAN training `_
* `Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network `_
* `YOLO9000: Better, Faster, Stronger `_ : détection en temps
d'objets sur des images ou dans une vidéo, le code est sur github
`darknet `_, wrapper Python :
`darknetpy `_,
`demo `_
* `SSD: Single Shot MultiBox Detector `_
(voir aussi `caffe/ssd `_)
* `HPatches: A benchmark and evaluation of handcrafted and learned local descriptors `_
* `Learning Transferable Architectures for Scalable Image Recognition `_
*Algorithmes*
* `Viola–Jones object detection framework `_
* `Histograms of Oriented Gradients for Human Detection (HOG) `_
* `One Millisecond Face Alignment with an Ensemble of Regression Trees `_,
`Github/AndrejMaris/facefit `_
* `ageitgey/step-2a_finding-face-landmarks.py `_
*Outils*
* `Image Descriptors `_,
`Speeded up robust features (SURF) `_,
`Scale-invariant feature transform (SIFT) `_,
*Modules*
* `VIGRA `_
* `opencv `_
* `dlib `_
* `hed `_ (Holistically-Nested Edge Detection)
* `bob.bio `_
* tous les modules de :ref:`l-deep-learning`
* `plat `_
(Utilities for exploring generative latent spaces as described in the
`Sampling Generative Networks `_ paper.)
* `darknetpy `_
*Modèles pré-entraînés*
* `VGG16 model for Keras `_,
`VGG in TensorFlow `_,
`Very Deep Convolutional Networks for Large-Scale Visual Recognition `_