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Biomimetics > Lecture 10 & 11 > Flashcards

Lecture 10 & 11 Flashcards

1
Q

What are steerable filters? What are they most useful for?

A

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2
Q

What is Cortexica?

A

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3
Q

What is the basis from “Where’s Wally?” What areas of the brain are involved?

A

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4
Q

How does the John Lewis app work? What does it use?

A

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5
Q

What are the different components of the macroscopic view of the visual system?

A

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6
Q

What is RGC? What is LGN?

A

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7
Q

What is the function of the LGN?

A

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8
Q

What is the function of V1? What makes it so special?

A

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9
Q

What is the retinal structure like microscopically? What is so special? What does this mean for the function?

A

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10
Q

What are the different layers? What are their properties generally?

A

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11
Q

What is the structure of the cortex?

A

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12
Q

How to describe neuron behaviour?

A

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13
Q

What is STA?

A

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14
Q

What is reverse correlation?

A

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15
Q

What is a receptive field?

A

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16
Q

What is the response of a single cell to the orientation to the bar? What was this experiment?

A

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17
Q

What is the map of multiple cells? How is it organised? What is an important property?

A

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18
Q

What are the differences in the different layers of the visual cortex (V1)?

A

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19
Q

What is the different in circular variance in V1?

A

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20
Q

What are the different types of cells? How are they classified? How are they sorted in the layers?

A

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21
Q

What are the repeating pattern for layers of neurons?

A

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22
Q

What are the repeating pattern for single neurons?

A

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23
Q

What kind of patterns are needed to build an algorithm that represents the biological visual system?

A

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24
Q

How do the cells of V2 and V4 respond to different structures?

A

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25
Q

What were the different machine learning over the years?

A

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26
Q

What were the properties of the Granlund?

A

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27
Q

What were the properties of the Neocognitron?

A

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28
Q

What were the properties of the LeNet?

A

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29
Q

What were the properties of the AlexNet?

A

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30
Q

What is convolution? What does it do?

A

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31
Q

What is the linear component?

A

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32
Q

What is the non-linear component?

A

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33
Q

What is the activation function?

A

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34
Q

What is the bias?

A

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35
Q

What did AlexNet do? What can it do?

A

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36
Q

What was the planned architecture?

A

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37
Q

What changed in it to make it a more realistic architecture?

A

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38
Q

What is the multilayer convolution system? How does it work? What are the stages?

A

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39
Q

How is training done in a multilayer convolution system?

A

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40
Q

How does AlexNet work? What ways is it similar?

A

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41
Q

What are the receptive fields in the artificial networks at different levels? How do they compare to biological networks?

A

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42
Q

What is the computational heavy part? What is a consequence of this?

A

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43
Q

What was the solution to this which was used in Cortexica?

A

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44
Q

How to synthesise the effective response to different types of spatial phase without using significant amounts of computation? What is the limitation?

A

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45
Q

How is the fingerprint like structure used in the John Lewis app?

A

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46
Q

How can you synthesise the effective response to all different angles?

A

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47
Q

What is the general summary of Steerable filters?

A

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Biomimetics (17 decks)

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