Domain adaptation and fusion using weakly supervised target irrelevant data
Номер патента: EP3610415A1
Опубликовано: 19-02-2020
Автор(ы): Jan Ernst, Kuan-Chuan Peng, Ziyan Wu
Принадлежит: Siemens Mobility GmbH
Опубликовано: 19-02-2020
Автор(ы): Jan Ernst, Kuan-Chuan Peng, Ziyan Wu
Принадлежит: Siemens Mobility GmbH
Реферат: Aspects include receiving a request to perform an image classification task in a target domain. The image classification task includes identifying a feature in images in the target domain. Classification information related to the feature is transferred from a source domain to the target domain. The transferring includes receiving a plurality of pairs of task-irrelevant images that each includes a task-irrelevant image in the source domain and in the target domain. The task-irrelevant image in the source domain has a fixed correspondence to the task-irrelevant image in the target domain. A target neural network is trained to perform the image classification task in the target domain. The training is based on the plurality of pairs of task-irrelevant images. The image classification task is performed in the target domain and includes applying the target neural network to an image in the target domain and outputting an identified feature.
Unsupervised domain adaptation method, device, system and storage medium of semantic segmentation based on uniform clustering
Номер патента: US11734390B2. Автор: Yingchun YANG,Ge Su,Shuiguang Deng,Jianwei Yin,Yongheng Shang. Владелец: Zhejiang University ZJU. Дата публикации: 2023-08-22.