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 Learningand TensorFlowEpisode 3 Deep Convolutional Neural Networks
Università degli Studi di Pavia
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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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[5]Deep Learning: a theoretical introduction – Episode 3
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The Mother of all DCNNs
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[6]Deep Learning: a theoretical introduction – Episode 3
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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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[9]Deep Learning: a theoretical introduction – Episode 3
Convolutional Layer▪
i
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[10]Deep Learning: a theoretical introduction – Episode 3
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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[13]Deep Learning: a theoretical introduction – Episode 3
Local Response Normalization Layer▪
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[14]Deep Learning: a theoretical introduction – Episode 3
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AlexNet Architecture
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[15]Deep Learning: a theoretical introduction – Episode 3
AlexNet Gradient▪
Loss Function
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[16]Deep Learning: a theoretical introduction – Episode 3
Convolutional Layer Gradient▪
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[17]Deep Learning: a theoretical introduction – Episode 3
Convolutional Layer Gradient▪
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[18]Deep Learning: a theoretical introduction – Episode 3
Convolutional Layer Gradient▪
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[19]Deep Learning: a theoretical introduction – Episode 3
Convolutional Layer Gradient▪
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[20]Deep Learning: a theoretical introduction – Episode 3
Convolutional Layer Gradient▪
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[21]Deep Learning: a theoretical introduction – Episode 3
Convolutional Layer Gradient▪
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[22]Deep Learning: a theoretical introduction – Episode 3
Convolutional Layer Gradient▪
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[23]Deep Learning: a theoretical introduction – Episode 3
Convolutional Layer Gradient▪
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[24]Deep Learning: a theoretical introduction – Episode 3
Convolutional Layer Gradient▪
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[25]Deep Learning: a theoretical introduction – Episode 3
Convolutional Layer Gradient▪
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ReLU
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[26]Deep Learning: a theoretical introduction – Episode 3
Max Pooling Gradient▪
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[27]Deep Learning: a theoretical introduction – Episode 3
Convolutional Layer Gradient▪
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[28]Deep Learning: a theoretical introduction – Episode 3
Convolutional Layer Gradient▪
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[29]Deep Learning: a theoretical introduction – Episode 3
LRN Gradient▪
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[30]Deep Learning: a theoretical introduction – Episode 3
LRN Gradient▪
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[31]Deep Learning: a theoretical introduction – Episode 3
LRN Gradient▪
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Yijl
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[32]Deep Learning: a theoretical introduction – Episode 3
LRN Gradient▪
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LRN
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X
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[33]Deep Learning: a theoretical introduction – Episode 3
ImageNet Challenge▪
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[34]Deep Learning: a theoretical introduction – Episode 3
AlexNet (Krizhevsky, Sutskever & Hinton, 2012)
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[35]Deep Learning: a theoretical introduction – Episode 3
Deep Convolutional Neural Networks (DCNN)▪
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[36]Deep Learning: a theoretical introduction – Episode 3
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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[45]Deep Learning: a theoretical introduction – Episode 3
Inception Acrhitecture▪
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[46]Deep Learning: a theoretical introduction – Episode 3
Inception Architecture▪
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[47]Deep Learning: a theoretical introduction – Episode 3
Inception Architecture▪
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[48]Deep Learning: a theoretical introduction – Episode 3
Inception Architecture▪
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[49]Deep Learning: a theoretical introduction – Episode 3
Inception Architecture▪
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[50]Deep Learning: a theoretical introduction – Episode 3
Inception Architecture▪
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[51]Deep Learning: a theoretical introduction – Episode 3
Inception Architecture▪
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[52]Deep Learning: a theoretical introduction – Episode 3
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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[56]Deep Learning: a theoretical introduction – Episode 3
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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[59]Deep Learning: a theoretical introduction – Episode 3
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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[64]Deep Learning: a theoretical introduction – Episode 3
The Power of Abstraction(in layers)
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[65]Deep Learning: a theoretical introduction – Episode 3
▪
The Power of Abstraction
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[66]Deep Learning: a theoretical introduction – Episode 3
▪
The Power of Abstraction
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[67]Deep Learning: a theoretical introduction – Episode 3
Mixing Two Images▪
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[68]Deep Learning: a theoretical introduction – Episode 3
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The Power of Abstraction
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[69]Deep Learning: a theoretical introduction – Episode 3
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The Power of Abstraction
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[70]Deep Learning: a theoretical introduction – Episode 3
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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[73]Deep Learning: a theoretical introduction – Episode 3
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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[83]Deep Learning: a theoretical introduction – Episode 3
Semantic segmentation
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[84]Deep Learning: a theoretical introduction – Episode 3
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▪