US 11,914,688 B2
Electronic device and controlling method of electronic device for identifying transition suitability of a neural network model included in an external device
Jaehong Kim, Suwon-si (KR); Juyong Song, Suwon-si (KR); Hyunjoo Jung, Suwon-si (KR); and Jungwook Kim, Suwon-si (KR)
Assigned to Samsung Electronics Co., Ltd., Suwon-si (KR)
Filed by Samsung Electronics Co., Ltd., Suwon-si (KR)
Filed on Dec. 7, 2020, as Appl. No. 17/113,615.
Claims priority of provisional application 62/945,349, filed on Dec. 9, 2019.
Claims priority of application No. 10-2020-0127461 (KR), filed on Sep. 29, 2020.
Prior Publication US 2021/0174137 A1, Jun. 10, 2021
Int. Cl. G06V 10/764 (2022.01); G06V 10/82 (2022.01); G06F 21/31 (2013.01); G06F 8/61 (2018.01); G06F 18/20 (2023.01); G06N 3/045 (2023.01)
CPC G06F 21/31 (2013.01) [G06F 8/61 (2013.01); G06F 18/285 (2023.01); G06N 3/045 (2023.01); G06V 10/764 (2022.01); G06V 10/82 (2022.01)] 20 Claims
OG exemplary drawing
 
1. An electronic device for identifying transition suitability of neural network models included in an external device, the electronic device comprising:
a communicator;
a memory configured to store first device information on a hardware specification of the electronic device and a hardware suitability identifier that identifies a neural network model suitable for hardware of the electronic device; and
a processor configured to:
control the communicator to transmit a first signal for requesting information related to one or more neural network models included in one or more external devices, based on a user input being received,
receive a second signal comprising second device information on a hardware specification of a first external device and first model information on one or more neural network models included in the first external device from the first external device among the one or more external devices through the communicator, as a response to the first signal,
identify whether each of the one or more neural network models included in the first external device is suitable for the hardware of the electronic device by inputting the first device information, the second device information, and the first model information into a hardware suitability identifier,
control the communicator to transmit a third signal comprising a request for installation data of one or more neural network models identified as suitable for the hardware of the electronic device to the first external device, and
receive a fourth signal comprising the installation data of the one or more neural network models identified as suitable for the hardware of the electronic device from the first external device through the communicator, as a response to the third signal,
wherein the processor is further configured to:
identify the one or more neural network models included in the first external device as suitable for the hardware of the electronic device, based on a specification of each of a plurality of hardware configurations included in the electronic device being greater than or equal to specifications of a plurality of hardware configurations included in the first external device, and
identify one or more neural network models having a hardware requirement specification lower than the specifications of the plurality of hardware configurations included in the electronic device among the one or more neural network models included in the first external device as suitable for the hardware of the electronic device, based on specifications of one or more of the plurality of hardware configurations included in the electronic device being less than the specifications of the plurality of hardware configurations included in the first external device.