Patent ID: 11914688
Assignee: SAMSUNG ELECTRONICS CO., LTD.
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 16:
17. A non-transitory computer readable recording medium comprising a program for executing a controlling method of an electronic device that stores 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 identifies transition suitability of neural network models included in an external device, wherein the controlling method includes:
transmitting a first signal for requesting information related to one or more neural network models included one or more external devices, based on a user input being received;
receiving 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, as a response to the first signal;
identifying 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;
transmitting 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
receiving 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, as a response to the third signal,
wherein the identifying whether each of the one or more neural network models is suitable for the hardware of the electronic device comprises:
identifying 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
identifying 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.