VISUALIZING DEEP NEURAL NETWORKS

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United States of America Patent

SERIAL NO

15584984

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Abstract

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Deep neural networks can be visualized. For example, first values for a first layer of nodes in a neural network, second values for a second layer of nodes in the neural network, and/or third values for connections between the first layer of nodes and the second layer of nodes can be received. A quilt graph can be output that includes (i) a first set of symbols having visual characteristics representative of the first values and representing the first layer of nodes along a first axis; (ii) a second set of symbols having visual characteristics representative of the second values and representing the second layer of nodes along a second axis; and/or (iii) a matrix of blocks between the first axis and the second axis having visual characteristics representative of the third values and representing the connections between the first layer of nodes and the second layer of nodes.

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Patent Owner(s)

Patent OwnerAddress
NORTH CAROLINA STATE UNIVERSITY1021 MAIN CAMPUS DRIVE 2ND FLOOR RALEIGH NC 27606

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Inventor(s)

Inventor Name Address # of filed Patents Total Citations
BENSON, JORDAN RILEY Ellerbe, US 17 287
CAIRA, DAVID JAMES Chapel Hill, US 8 104
COX, JAMES ALLEN Cary, US 46 2101
DEVARAJAN, RAVINDER Cary, US 13 188
HEALEY, CHRISTOPHER GRAHAM Cary, US 4 54
LEEMAN-MUNK, SAMUEL PAUL Cary, US 11 266
LEWIS, LAWRENCE E Raleigh, US 9 191
NIE, SHAOLIANG Raleigh, US 5 71
PADIA, KALPESH Raleigh, US 7 103
SETHI, SARATENDU Raleigh, US 21 311

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