Feb 28, 2020 · While the P-CNN is trained with the CAM guided cropped image patches and is used to capture local-scale information of skin lesion regions.

Abstract—Precise skin lesion classification is still challenging due to two problems, i.e., (1) inter-class similarity and intra-class.

For instance, Tang et al. [19] proposed a GP-CNN model, which improved the classification performance of skin lesions by combining global and local feature ...

Oct 5, 2020 · In this paper, we propose a global-part model with color constant ensemble learning for the skin lesion classification. Quantitative and ...

A Global-Part Convolutional Neural Network (GP-CNN) model, which treats the fine-grained local information and global context information with equal ...

Dive into the research topics of 'GP-CNN-DTEL: Global-Part CNN Model with Data-Transformed Ensemble Learning for Skin Lesion Classification'. Together they form ...

Dive into the research topics of 'GP-CNN-DTEL: Global-Part CNN Model with Data-Transformed Ensemble Learning for Skin Lesion Classification'. Together they form ...

A Global-Part Convolutional Neural Network (GP-CNN) model, which treats the fine-grained local information and global context information with equal ...

Precise skin lesion classification is still challenging due to two problems, i.e., (1) inter-class similarity and intra-class variation of skin lesion ...

Co-authors ; GP-CNN-DTEL: Global-part CNN model with data-transformed ensemble learning for skin lesion classification. P Tang, Q Liang, X Yan, S Xiang, D Zhang.