Deep Learning and TensorFlow...Deep Learning: a theoretical introduction –Episode 3 [1]Deep...

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[1] Deep Learning: a theoretical introduction – Episode 3 Deep Learning and TensorFlow Episode 3 Deep Convolutional Neural Networks Università degli Studi di Pavia

Transcript of Deep Learning and TensorFlow...Deep Learning: a theoretical introduction –Episode 3 [1]Deep...

Page 1: Deep Learning and TensorFlow...Deep Learning: a theoretical introduction –Episode 3 [1]Deep Learning and TensorFlow Episode 3 Deep Convolutional Neural Networks Università degli

[1]Deep Learning: a theoretical introduction – Episode 3

Deep Learningand TensorFlowEpisode 3 Deep Convolutional Neural Networks

Università degli Studi di Pavia

http://vision.unipv.it/AI/AIRG.html
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[2]Deep Learning: a theoretical introduction – Episode 3

The storm ofDeep Convolutional Neural Networks

(DCNN)

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[3]Deep Learning: a theoretical introduction – Episode 3

ImageNet Challenge▪

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[4]Deep Learning: a theoretical introduction – Episode 3

ImageNet Challenge▪

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The Mother of all DCNNs

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The Mother of all DCNNs

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[7]Deep Learning: a theoretical introduction – Episode 3

DCNN Building Blocks(layerwise)

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[8]Deep Learning: a theoretical introduction – Episode 3

Convolutional Layer▪

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Convolutional Layer▪

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Convolutional Layer▪

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[11]Deep Learning: a theoretical introduction – Episode 3

Convolutional Layer▪

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[12]Deep Learning: a theoretical introduction – Episode 3

Max Pooling Layer▪

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Local Response Normalization Layer▪

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AlexNet Architecture

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AlexNet Gradient▪

Loss Function

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[16]Deep Learning: a theoretical introduction – Episode 3

Convolutional Layer Gradient▪

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0,0

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Convolutional Layer Gradient▪

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Convolutional Layer Gradient▪

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Convolutional Layer Gradient▪

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Convolutional Layer Gradient▪

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Convolutional Layer Gradient▪

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Convolutional Layer Gradient▪

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Convolutional Layer Gradient▪

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Convolutional Layer Gradient▪

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ReLU

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Convolutional Layer Gradient▪

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ReLU

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Max Pooling Gradient▪

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Convolutional Layer Gradient▪

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Convolutional Layer Gradient▪

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LRN Gradient▪

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LRN Gradient▪

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LRN Gradient▪

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LRN Gradient▪

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ImageNet Challenge▪

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AlexNet (Krizhevsky, Sutskever & Hinton, 2012)

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Deep Convolutional Neural Networks (DCNN)▪

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Inside AlexNet(after training)

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[37]Deep Learning: a theoretical introduction – Episode 3

AlexNet Filters (after training)

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[38]Deep Learning: a theoretical introduction – Episode 3

AlexNet Filters- DeconvNet

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[39]Deep Learning: a theoretical introduction – Episode 3

AlexNet Filters- DeconvNet

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[40]Deep Learning: a theoretical introduction – Episode 3

AlexNet Filters- DeconvNet

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[41]Deep Learning: a theoretical introduction – Episode 3

AlexNet Filters- DeconvNet

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[42]Deep Learning: a theoretical introduction – Episode 3

Beyond AlexNet:The DCNN storm

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[43]Deep Learning: a theoretical introduction – Episode 3

ImageNet: the full story

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[44]Deep Learning: a theoretical introduction – Episode 3

VGG Architecture

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Inception Acrhitecture▪

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[46]Deep Learning: a theoretical introduction – Episode 3

Inception Architecture▪

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Inception Architecture▪

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Inception Architecture▪

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Inception Architecture▪

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Inception Architecture▪

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Inception Architecture▪

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ResNet Architecture▪

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[53]Deep Learning: a theoretical introduction – Episode 3

ResNet Architecture▪

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[54]Deep Learning: a theoretical introduction – Episode 3

Comparing Different DCNNs▪

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[55]Deep Learning: a theoretical introduction – Episode 3

Comparing Different DCNNs

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Do DCNNs Dreamof Electric Sheep?

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[57]Deep Learning: a theoretical introduction – Episode 3

Can DCNNs 'dream'?

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[58]Deep Learning: a theoretical introduction – Episode 3

Can DCNNs 'dream'?

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Feature Enhancement▪

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[60]Deep Learning: a theoretical introduction – Episode 3

Can DCNNs 'dream'?

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[61]Deep Learning: a theoretical introduction – Episode 3

Can DCNNs 'dream'?

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[62]Deep Learning: a theoretical introduction – Episode 3

Can DCNNs 'dream'?

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[63]Deep Learning: a theoretical introduction – Episode 3

Can DCNNs 'dream'?

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The Power of Abstraction(in layers)

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The Power of Abstraction

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The Power of Abstraction

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Mixing Two Images▪

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The Power of Abstraction

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The Power of Abstraction

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Human-like Vision?

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[71]Deep Learning: a theoretical introduction – Episode 3

A DCNN can be fooled…

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[72]Deep Learning: a theoretical introduction – Episode 3

Reconstructing Images from Feature Maps

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Reconstructing Images from Feature Maps▪

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[74]Deep Learning: a theoretical introduction – Episode 3

Reconstructing Images from Feature Maps

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[75]Deep Learning: a theoretical introduction – Episode 3

Just add some little noise ...

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[76]Deep Learning: a theoretical introduction – Episode 3

No Free Lunch:having an annotated dataset

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[77]Deep Learning: a theoretical introduction – Episode 3

Generative Adversarial Network▪

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[78]Deep Learning: a theoretical introduction – Episode 3

Active Learning

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[79]Deep Learning: a theoretical introduction – Episode 3

Transfer Learning

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[80]Deep Learning: a theoretical introduction – Episode 3

Transfer Learning

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[81]Deep Learning: a theoretical introduction – Episode 3

Image ClassificationObject Detection

Segmentation

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[82]Deep Learning: a theoretical introduction – Episode 3

Deep Learning for different imaging tasks

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Semantic segmentation

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Object detection and positioning

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[85]Deep Learning: a theoretical introduction – Episode 3

Object detection and positioning

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[86]Deep Learning: a theoretical introduction – Episode 3

Object detection and positioning▪


TensorFlow with Apache Ignite and Machine and Deep ... · Achieving Continuous Machine and Deep Learning with Apache Ignite and TensorFlow Yuriy Babak 2019 © GridGain Systems

TensorFlow with Apache Ignite and Machine and Deep ... · Achieving Continuous Machine and Deep Learning with Apache Ignite and TensorFlow Yuriy Babak 2019 © GridGain Systems

Deep Learning with Keras and TensorFlow

Deep Learning with Keras and TensorFlow

Deep Learning for Computer Vision with Tensorflow · What is TensorFlow? •TensorFlow was originally developed by researchers and engineers working on the Google Brain Team. •TensorFlow

Deep Learning for Computer Vision with Tensorflow · What is TensorFlow? •TensorFlow was originally developed by researchers and engineers working on the Google Brain Team. •TensorFlow

Università degli Studi di Pavia Deep Learning and TensorFlow · Deep Learning and TensorFlow –Episode 4 [1] Deep Learning and TensorFlow Episode 4 TensorFlow Basics Part 1 Università

Università degli Studi di Pavia Deep Learning and TensorFlow · Deep Learning and TensorFlow –Episode 4 [1] Deep Learning and TensorFlow Episode 4 TensorFlow Basics Part 1 Università

TensorFlow and Keras - Statinfer...Contents •Deep Learning frameworks •What is TensorFlow •Key terms in TensorFlow •Working with TensorFlow •Regression Model building •MNIST

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Deep Learning, Keras, and TensorFlow

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Deep Learning: R with Keras and TensorFlow

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Visualizing Dataflow Graphs of Deep Learning Models in TensorFlow · 3 BACKGROUND: TENSORFLOW TensorFlow [6] is Google’s system for the implementation and deploy-ment of large-scale

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Introduction to TensorFlow 2...Deep Learning Intro to TensorFlow TensorFlow @ Google 2.0 and Examples Getting Started TensorFlow Deep Learning Doodles courtesy of @dalequark Weight

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Introduction to tensorflow · Introduction to tensorflow. Why do you need a deep learning framework? Speed: ... - Deep-learning/Machine learning specific - Simpler to do common tasks.

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Learning in TensorFlow Deep ReinforcementLearning in TensorFlow Danijar Hafner · Stanford CS 20SI · 2017-03-10. Gu16. Barron16. Hafner16. Repeat until end of episode: Most methods

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Deep-Learning-TensorFlow Documentation - Read the · PDF fileDeep-Learning-TensorFlow Documentation, Release latest Thisprojectis a collection of various Deep Learning algorithms implemented

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EMPIRICAL STUDY OF DEEP NEURAL NETWORK …dslsrv1.rnet.missouri.edu/~shangy/Thesis/MingDu.pdfTheano. TensorFlow[8] is a python deep learning framework create by Google. Using TensorFlow,

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Deep Learning avec TensorFlow - Dunod · VIII Deep Learning avec TensorFlow clientèle en fonction de la date, de l’heure et de mille autres paramètres, etc. La liste d’applications

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