DigitRecognizer | Java Convolutional Neural Network example | Machine Learning library

by klevis Java Version: Current License: No License

X-Ray Key Features Code Snippets Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | DigitRecognizer Summary

DigitRecognizer is a Java library typically used in Artificial Intelligence, Machine Learning, Deep Learning applications. DigitRecognizer has no bugs, it has no vulnerabilities, it has build file available and it has low support. You can download it from GitHub.

Java Convolutional Neural Network example for Hand Writing Digit Recognition

Support

Quality

Security

License

Reuse

Support

DigitRecognizer has a low active ecosystem.

It has 23 star(s) with 24 fork(s). There are 5 watchers for this library.

It had no major release in the last 6 months.

There are 4 open issues and 6 have been closed. On average issues are closed in 2 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of DigitRecognizer is current.

Quality

DigitRecognizer has 0 bugs and 0 code smells.

Security

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

DigitRecognizer code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

DigitRecognizer 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

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

Build file is available. You can build the component from source.

DigitRecognizer saves you 550 person hours of effort in developing the same functionality from scratch.

It has 1288 lines of code, 66 functions and 16 files.

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

Top functions reviewed by kandi - BETA

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

Start the application
Creates an array of labeled images
Add the top - left panel
Add an action panel to the result panel
Applies the 2D convolution of the input image
Applies a single pixel - level convolution at a certain position
2D convolution function
Paint the component
Clear the canvas
Applies the convolution algorithm
Performs a 2D convolution across the image
Calculates the current score for the network
Main method for testing
Apply convolution
Converts a double array to a valid RGB array
Computes a 2D double - level kernel
Initializes Spark Session

Get all kandi verified functions for this library.

DigitRecognizer Key Features

No Key Features are available at this moment for DigitRecognizer.

DigitRecognizer Examples and Code Snippets

No Code Snippets are available at this moment for DigitRecognizer.

Community Discussions

Trending Discussions on DigitRecognizer

Java, Android, camerax programming. Error: cannot find symbol. symbol: class Builder

QUESTION

Java, Android, camerax programming. Error: cannot find symbol. symbol: class Builder

Asked 2020-Mar-23 at 21:51

I am try to take a picture with an Android smartphone by using the camerax libary from Android.
I am following their tutorial to capture images. First I need to initalize the ImageCapturer:

...

ANSWER

Answered 2020-Mar-23 at 21:51

You're using the alpha06 version of the camerax core artifact, building a use case using the use case's builder was introduced in version07 of camerax core. For alpha06, you had to write:

Source https://stackoverflow.com/questions/60821146

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

Vulnerabilities

No vulnerabilities reported

Install DigitRecognizer

You can download it from GitHub.
You can use DigitRecognizer 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 DigitRecognizer 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 .

Find more information at: