Ensemble architecture in polyp segmentation

• URL: http://arxiv.org/abs/2408.07262v3
• Date: Fri, 25 Oct 2024 02:00:22 GMT
• Title: Ensemble architecture in polyp segmentation
• Authors: Hao-Yun Hsu, Yi-Ching Cheng, Guan-Hua Huang,
• Abstract summary: This study explores the architecture of semantic segmentation and evaluated models that excel in polyp segmentation. We present an integrated framework that harnesses the advantages of different models to attain an optimal outcome.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: This study explored the architecture of semantic segmentation and evaluated models that excel in polyp segmentation. We present an integrated framework that harnesses the advantages of different models to attain an optimal outcome. Specifically, in this framework, we fuse the learned features from convolutional and transformer models for prediction, thus engendering an ensemble technique to enhance model performance. Our experiments on polyp segmentation revealed that the proposed architecture surpassed other top models, exhibiting improved learning capacity and resilience. The code is available at https://github.com/HuangDLab/EnFormer.

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