sevarac - Slashdot User

Comment Re:This wont work... (Score 1) 98

by sevarac on Tuesday October 13, 2009 @02:58PM (#29735205) Attached to: Image Recognition Neural Networks, Open Sourced

1. What if you want to classify pictures that have different sizes (not too uncommon)? Wont work because you first have to set a fixed number of neurons in your first layer.

All images are scaled to the same dimensions determined by the sample resolution settings.

2. What about different locations of the same object?

This problem is not adresed here. Suggested approach can be used on whole images or specific known image locations.

Comment Re:!Open Sourced (Score 1) 98

by sevarac on Tuesday October 13, 2009 @02:33PM (#29734925) Attached to: Image Recognition Neural Networks, Open Sourced

Hi, you're right when you say the Neuroph has always been open source, but the image recognition used by http://dota-autoscript.com/ has not been open source. With this release of Neuroph we added the image recognition support based on ideas and original code from http://dota-autoscript.com./

Submission + - Image Recognition Neural Networks (sourceforge.net)

Submitted by sevarac on Sunday October 11, 2009 @09:40PM

sevarac writes: The latest release of Java Neural Network Framework Neuroph v2.3 comes with ready-to-use image recognition support. It provides GUI tool for training multi layer perceptrons for image recognition, and easy to use API to deploy these neural networks in end-user applications. This image recognition approach has been successfully used by DotA AutoScript tool, and now it is released as open source. With this Java library basic image recognition can be performed in just few lines of code. The developers have published howto article and online demo which can be used to train image recognition neural networks online.

Java Program Uses Neural Networks To Monitor Games 100

Posted by Soulskill on Thursday May 14, 2009 @02:13AM from the automating-the-automation dept.

tr0p writes "Java developers have used the open source Neuroph neural network framework to monitor video game players while they play and then provide helpful situational awareness, such as audio queues when a power-up is ready or on-the-fly macros for combo attacks. The developers have published an article describing many of the technical details of their implementation. 'There are two different types of neural networks used by DotA AutoScript. The first type is a simple binary image classifier. It uses Neuroph's "Multi-Layer Perceptron" class to model a neural network with an input neurons layer, one hidden neurons layer, and an output neurons layer. Exposing an image to the input layer neurons causes the output layer neurons to produce the probability of a match for each of the images it has been trained to identify; one trained image per output neuron.'"

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