neurogear | Object-Oriented convolutional neural network library

by Foxbud Java Version: Current License: No License

X-Ray Key Features Code Snippets Community Discussions Vulnerabilities Install Support

kandi X-RAY | neurogear Summary

neurogear is a Java library. neurogear has no bugs, it has no vulnerabilities and it has low support. However neurogear build file is not available. You can download it from GitHub.

Object-Oriented convolutional neural network library written in Java. Please contact the author, Garrett Fairburn, via breadboardfox@gmail.com.

Support

Quality

Security

License

Reuse

Support

neurogear 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.

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

It has a neutral sentiment in the developer community.

The latest version of neurogear is current.

Quality

neurogear has 0 bugs and 0 code smells.

Security

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

neurogear code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

neurogear 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

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

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

It has 1456 lines of code, 161 functions and 53 files.

It has medium code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

kandi has reviewed neurogear and discovered the below as its top functions. This is intended to give you an instant insight into neurogear implemented functionality, and help decide if they suit your requirements.

Main entry point .
Computes scaling factors .
Test whether we should re -ceptive field conflicts .
Remove a datum from the data array .
Propagates this connection .
Generate weights for network connections .
Correct the weight .
Test for exceptions .
Returns the value for the given sum .
Set initial node delta .

Get all kandi verified functions for this library.

neurogear Key Features

No Key Features are available at this moment for neurogear.

neurogear Examples and Code Snippets

No Code Snippets are available at this moment for neurogear.

Community Discussions

No Community Discussions are available at this moment for neurogear.Refer to stack overflow page for discussions.

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install neurogear

You can download it from GitHub.
You can use neurogear like any standard Java library. Please include the the jar files in your classpath. You can also use any IDE and you can run and debug the neurogear component as you would do with any other Java program. Best practice is to use a build tool that supports dependency management such as Maven or Gradle. For Maven installation, please refer maven.apache.org. For Gradle installation, please refer gradle.org .

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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