公开(公告)号：US12254348B2

公开(公告)日：2025-03-18

申请号：US18090639

申请日：2022-12-29

Applicant: Panasonic Intellectual Property Management Co., Ltd.

Inventor： Masaki Takahashi ,  Yohei Nakata ,  Yasunori Ishii ,  Tomoyuki Okuno

IPC: G06F9/48

Abstract: An information processing apparatus includes: an obtainer that obtains sensing data; a common neutral network (NN) that inputs the sensing data into an inference model to obtain a result of inference and information on a processing time for a plurality of tasks subsequent to the processing performed by the inference model; and an NN inference computation management unit that determines a task schedule for a task processing unit that processes the plurality of subsequent tasks to process the plurality of subsequent tasks on the basis of the information on the processing time for the plurality of subsequent tasks and inputs the result of the inference into the task processing unit to process the plurality of subsequent tasks according to the determined task schedule.

公开(公告)号：US11270228B2

公开(公告)日：2022-03-08

申请号：US16168664

申请日：2018-10-23

Applicant: Panasonic Intellectual Property Management Co., Ltd.

Inventor： Yohei Nakata

IPC: G06N20/00 ,  G06N3/04 ,  G06N3/08 ,  G06N3/063 ,  G06F9/445

Abstract: An information processing method includes: deciding a configuration of a machine learning model, using a processor; performing first determination as to whether the machine learning model in the decided configuration meets a first performance requirement on hardware performance; performing learning using the machine learning model in the configuration determined to meet the first performance requirement, performing second determination as to whether a learned model obtained by the learning meets a second performance requirement on evaluation value of output of a machine learning model, and when the learned model is determined to meet the second performance requirement, outputting information indicating that both performance requirements are met; and when it is determined that the first performance requirement is not met, changing the configuration of the machine learning model, and performing the first determination as to whether the machine learning model in the changed configuration meets the first performance requirement.