Mela_DNN An integrated method based on deep convolutional neural network to recognize melanoma
Introduction
Our software contains an integrated method based on deep convolutional neural network to recognize melanoma. We first crop the original images using segmentation masks which are generated from segmentation network, then we use five state-of-the-art networks to extract features, and add SE block to the network to help highlight more effective features. Finally, we construct a new neural network use local connection to integrate the classification results of these models.
Publications
Credits
- Fei Guo fguo@tju.edu.cn Investigator
School of Computer Science and Technology, College of Intelligence and Computing, Tianjin University, China
- Jie Song songjie@tju.edu.cn Developer
School of Computer Science and Technology, College of Intelligence and Computing, Tianjin University, China
- Jiawei Li jiawei6636@tju.edu.cn Developer
School of Computer Science and Technology, College of Intelligence and Computing, Tianjin University, China
- Shiqiang Ma shiqiang@tju.edu.cn Developer
School of Computer Science and Technology, College of Intelligence and Computing, Tianjin University, China
- Jijun Tang tangjijun@tju,edu,cn Developer
School of Computer Science and Technology, College of Intelligence and Computing, Tianjin University, China
Community Ratings
Usability | Efficiency | Reliability | Rated By |
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0 user | |||
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Accession | BT007141 |
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Tool Type | Application |
Category | Data management and annotation |
Platforms | Linux/Unix |
Technologies | Python3 |
User Interface | Terminal Command Line |
Latest Release | 1.0 (May 31, 2021) |
Download Count | 797 |
Country/Region | China |
Submitted By | Fei Guo |
2018YFC0910400