kandi X-RAY | new-EM-Fisher-loss Summary
kandi X-RAY | new-EM-Fisher-loss Summary
new-EM-Fisher-loss is a Python library. new-EM-Fisher-loss has no bugs, it has no vulnerabilities and it has low support. However new-EM-Fisher-loss build file is not available. You can download it from GitHub.
一种新的损失函数，用于图像分割。该损失函数加入了边缘信息，并且使用了fisher准则，能够实现类间距离更大，类内距离更小（方差实现）。因为加入了方差，使得模型训练的更稳定。
一种新的损失函数，用于图像分割。该损失函数加入了边缘信息，并且使用了fisher准则，能够实现类间距离更大，类内距离更小（方差实现）。因为加入了方差，使得模型训练的更稳定。
Support
Quality
Security
License
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Support
new-EM-Fisher-loss has a low active ecosystem.
It has 0 star(s) with 0 fork(s). There are 1 watchers for this library.
It had no major release in the last 6 months.
new-EM-Fisher-loss has no issues reported. There are no pull requests.
It has a neutral sentiment in the developer community.
The latest version of new-EM-Fisher-loss is current.
Quality
new-EM-Fisher-loss has no bugs reported.
Security
new-EM-Fisher-loss has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
License
new-EM-Fisher-loss does not have a standard license declared.
Check the repository for any license declaration and review the terms closely.
Without a license, all rights are reserved, and you cannot use the library in your applications.
Reuse
new-EM-Fisher-loss releases are not available. You will need to build from source code and install.
new-EM-Fisher-loss has no build file. You will be need to create the build yourself to build the component from source.
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new-EM-Fisher-loss Key Features
No Key Features are available at this moment for new-EM-Fisher-loss.
new-EM-Fisher-loss Examples and Code Snippets
No Code Snippets are available at this moment for new-EM-Fisher-loss.
Community Discussions
No Community Discussions are available at this moment for new-EM-Fisher-loss.Refer to stack overflow page for discussions.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install new-EM-Fisher-loss
You can download it from GitHub.
You can use new-EM-Fisher-loss like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
You can use new-EM-Fisher-loss like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
Support
For any new features, suggestions and bugs create an issue on GitHub.
If you have any questions check and ask questions on community page Stack Overflow .
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