Mar 3, 2017 · The proposed multi-task learning model solves different tasks (eg, lesion segmentation and two independent binary lesion classifications) at the same time.
In this study, a multi-task deep neural network is proposed for skin lesion analysis. The proposed multi-task learning model solves different tasks (e.g., ...
A multi-task deep neural network that solves different tasks at the same time by exploiting commonalities and differences across tasks results in improved ...
(PDF) A Novel Multi-task Deep Learning Model for Skin Lesion ...
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The experimental results show that the proposed multi-task deep learning model achieves promising performances on skin lesion segmentation and classification.
In this paper, we propose a multi-task learning (MTL) network based on the label-level fusion of metadata and hand-crafted features by unsupervised clustering.
Jan 10, 2023 · A deep learning network approach based on pre-trained convolutional neural networks was developed for melanoma classification.
Jun 1, 2024 · The model can analyze 32,640 x 25,920 pixels images and demonstrate effective cell detection and segmentation, achieving a mAP0.5-0.95\ ...
A deep learning network approach based on pre-trained convolutional neural networks was developed for melanoma classification with dermoscopy images using ...
Feb 28, 2023 · In this paper, we propose a collaborative learning deep convolutional neural networks (CL-DCNN) model based on the teacher–student learning method for ...
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Nov 15, 2023 · In this paper, we propose an end-to-end multi-task learning convolutional neural network (MTL-CNN) for joint skin lesion segmentation and ...