Here's one our patent attorneys might have a look at:It converts...

Here's one our patent attorneys might have a look at:

It converts 8-bit CNN signals to single bits. Familiar?

US2020175351A1 BIT INTERPRETATION FOR CONVOLUTIONAL NEURAL NETWORK INPUT LAYERAvailable inPatent Translate

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Global Dossier

Applicants

BOSCH GMBH ROBERT [DE]

Inventors

DUERICHEN ROBERT [DE]; PETERS CHRISTIAN [US]; ROCZNIK THOMAS [US]

Classifications

IPC

G06N3/04; G06N3/08;

CPC

G06N3/04 (US); G06N3/0454 (EP,CN); G06N3/063 (EP,CN); G06N3/08 (US); G06N3/0445 (EP);

Priorities

US201816206622A·2018-11-30

Application

US201816206622A·2018-11-30

Publication

US2020175351A1·2020-06-04

Published as

CN111260023A;

EP3660747A1;

KR20200066215A;

US2020175351A1

EN

BIT INTERPRETATION FOR CONVOLUTIONAL NEURAL NETWORK INPUT LAYER

Abstract

To efficiently execute deep convolutional neural networks (CNN) on edge devices (e.g., wearable device like an Apple Watch or FitBit) it may be necessary to reduce the bit width of the network parameters down to 1-bit. Binarization at the first layer of a CNN has typically not been performed because it may lead to an increase in the output validation error of the input data. The method and systems provided include a binary input layer (BIL) which accepts binary input data by learning bit specific binary weights. By executing the CNN using binary input data, the present method and system may result in a reduction in the chip area consumed and the energy used in contrast to CNN models executed using floating point input data.