公开(公告)号：US20220092420A1

公开(公告)日：2022-03-24

申请号：US17480999

申请日：2021-09-21

Applicant: Intelligent Fusion Technology, Inc.

Inventor： Jingyang LU ,  Erik BLASCH ,  Roman ILIN ,  Hua-mei CHEN ,  Dan SHEN ,  Nichole SULLIVAN ,  Genshe CHEN

IPC: G06N3/08 ,  G06K9/62 ,  G06K9/00

Abstract: Embodiments of the present disclosure provide a method, a device, and a storage medium for domain adaptation for efficient learning fusion (DAELF). The method includes acquiring data from a plurality of data sources of a plurality of sensors; for each of the plurality of sensors, training an auxiliary classifier generative adversarial network (AC-GAN) by a hardware processor with data from each data source of the plurality of data sources, thereby obtaining a trained feature extraction network and a trained label prediction network for each data source; forming a decision-level fusion network or a feature-level fusion network; and training the decision-level fusion network or the feature-level fusion network with a source-only mode or a generate to adapt (GTA) mode; and applying the trained decision-level fusion network or the trained feature-level fusion network to detect a target of interest.