Inner Mongolia University of Technology

Yongsheng Qi

Jianqiang Su

Peiliang Chen

Liqiang Liu

Yongting Li

An image semantic segmentation algorithm and system based on multi-channel deep weighted aggregation where the image semantic segmentation algorithm is based on multi-channel deep weighted aggregation. The aggregation includes semantic features with definite class information in an image, transition semantic features between low-level semantic and high-level semantic, and semantic features of context logic relationship in an image are extracted by a low-level semantic channel, an auxiliary semantic channel and a high-level semantic channel, respectively. The aggregation further includes three different semantic features obtained in S1 are fused by weighted aggregation to obtain global semantic information of the image; S3, the semantic features output from respective semantic channels in S1 and the global semantic information in S2 are used to compute loss function for training.

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Hohhot, China

Yongsheng Qi