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Page 3
Image classification for crowdsourcing feature in mobile app
This is weather: it’s OK! This is not weather: not OK
CNN image classification, inception v3 + transfer learning
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Automatic text weather forecast
Reference situation
Quelques <précipitations <gouttes | flocons > 09> tombent <temps <au lever du jour | après le déjeuner>>. [...]
Bulletin du département du Gard (30) élaboré le 11 septembre 2018 à 06:45:00 TU
Pour demain mercredi 12 en journée,
Quelques gouttes tombent au lever du jour. Des averses à partir de la fin de matinée peuvent nécessiter l’usage du parapluie sous un ciel qui reste très nuageux. L’après-midi, ces averses peuvent localement prendre un caractère orageux, des Causses à l’Aigoual.
Text weather report
K-means for creation of reference situations
IN PRODUCTION!
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Detection of rain areas in weather model output
U-Net image segmentation
Credits: Lucie Rottner, Laure Raynaud, Philippe Arbogast
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Temperature correctionfor amateur weather stations
Ground truth: a Meteo-France weather stationInput features: 5 to 10 Netatmo weather stations nearby
Time series prediction with LSTM-RNN
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Predict next images
+5’+10’
+15’+20’
+25’+30’
+35’+40’
+45’+50’
+55’+60’
-10’-5’
-15’
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Model
We have traditional models: optical flow propagation.Can Deep Learning do better?
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Our architecture
+5’+10’
+15’+20’
+25’+30’
+35’+40’
+45’+50’
+55’
+60’
-10’-5’
-15’
0’
Con
v
Max
pool
Con
v
Con
v
Con
v
Con
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Brute force!
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Convolutions are not good at moving objects
Solution to investigate:translate objects first
t-15min
t+0min
Issue: convolution can’t see moving object on 2 input images
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Areas for improvement
■ For training time
― CNN are not very good at moving objects
=> hybridate an optical flow model and Deep Learning
― Run on a powerful GPU cluster
― Optimize architecture (autoencoder, multiscale, other kind of architectures more prone to moving objects...)
■ For blurring
― Try with a GAN (Generative Adverserial Network)
■ Work in progress for clouds nowcasting
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Meteo-France AI Lab
Until now : master interns
Acceleration of investments on AI
● Feb 2019:Creation of an AI Lab with a target of 6 experts in Data Science
● Oct 2019:Installation of a GPU cluster and fast storage infrastructure (400k€)
Funded by the FTAP (Public Action Transformation Fund)
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Meteo-France Github
● Formation deep-learning (en français !) :● https://github.com/meteofrance/formation-deep-learning