STEDPreferenceSNN | repo contains the neural network architecture

by PDKlab Python Version: Current License: MIT

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kandi X-RAY | STEDPreferenceSNN Summary

STEDPreferenceSNN is a Python library. STEDPreferenceSNN has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. However STEDPreferenceSNN build file is not available. You can download it from GitHub.

This repo contains the neural network architecture for learning a preference articulation function between several objectives. This is the SNN architecture presented used in the paper Toward intelligent nanoscopy: A machine learning approach for automated optimization of super-resolution optical microscopy. It contains the code for training a model from scratch, and deplyoing a model on a server using the Docker file.

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STEDPreferenceSNN has a low active ecosystem.

It has 0 star(s) with 0 fork(s). There are 2 watchers for this library.

It had no major release in the last 6 months.

STEDPreferenceSNN has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of STEDPreferenceSNN is current.

Quality

STEDPreferenceSNN has no bugs reported.

Security

STEDPreferenceSNN has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

STEDPreferenceSNN is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

STEDPreferenceSNN releases are not available. You will need to build from source code and install.

STEDPreferenceSNN has no build file. You will be need to create the build yourself to build the component from source.

Installation instructions are not available. Examples and code snippets are available.

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STEDPreferenceSNN Key Features

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STEDPreferenceSNN Examples and Code Snippets

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Community Discussions

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Vulnerabilities

No vulnerabilities reported

Install STEDPreferenceSNN

You can download it from GitHub.
You can use STEDPreferenceSNN 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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