- 专利标题: Method and system for semantic segmentation involving multi-task convolutional neural network
-
申请号: US16237069申请日: 2018-12-31
-
公开(公告)号: US10467500B1公开(公告)日: 2019-11-05
- 发明人: Ruxiao Bao , Xun Xu
- 申请人: DiDi Research America, LLC
- 申请人地址: US CA Mountain View
- 专利权人: DiDi Research America, LLC
- 当前专利权人: DiDi Research America, LLC
- 当前专利权人地址: US CA Mountain View
- 代理机构: Kikpatrick Townsend & Stockton LLP
- 主分类号: G06K9/00
- IPC分类号: G06K9/00 ; G06K9/62 ; G06K9/72 ; G06T9/00 ; G06T7/10 ; G06N3/08 ; G06T7/168
摘要:
Methods and systems involving convolutional neural networks as applicable for semantic segmentation, including multi-task convolutional networks employing curriculum based transfer learning, are disclosed herein. In one example embodiment, a method of semantic segmentation involving a convolutional neural network includes training and applying the convolutional neural network. The training of the convolutional neural network includes each of training a semantic segmentation decoder network of the convolutional neural network, generating first feature maps by way of an encoder network of the convolutional neural network, based at least in part upon a dataset received at the encoder network, and training an instance segmentation decoder network of the convolutional neural network based at least in part upon the first feature maps. The applying includes receiving an image, and generating each of a semantic segmentation map and an instance segmentation map in response to the receiving of the image, in a single feedforward pass.
信息查询