Image Recognition Neural Networks, Open Sourced 98
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 an 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 a howto article and an online demo which can be used to train image recognition neural networks online."
Usage of the comma, very weird (Score:3, Insightful)
What is it with Slashdot editors and this comma frenzy of theirs?
Re:Lots of tweaking required (in general) (Score:3, Insightful)
Furthermore you need plenty of training data partitioned into training and test sets so you can evaluate the generalisation error.
Yes. What's the alternative?
Working with neural nets has a mostly experimental feel to them
Most of software development is "experimental" because most software works with real-world data and because you have an endless cycle of implementing new features, testing, bug reporting, and bug fixing. With neural networks (and similar methods), at least people quantify their error rates. With most other applications, people can't even quantify how often they fail or whether a bug fix actually improves things.
Re:C/C++ implementation (Score:2, Insightful)
My issues with Java (and especially with the containers layered on top like Tomcat, J2EE etc) is simply resource usage. It can use up a lot of memory just to put a tiny little java app on a server. VMWare found this out when they rewrte their management utility using Tomcat, a lot of users started to complain that it took up 500mb, which was enough to run another guest image!
My other issue is the 100% pure java nonsense. Anyone that tries to tell me what languages I should code in gets that language added to my ban list. I know it was a reaction to MS, but other managed languages are roughly the same - you have to code in that managed environment or suffer various hacks, performance issues to get native code working, which in this day of easy-to-code script languages calling high-performance C dlls is just unacceptable.
Now, there are times when a C port is useful, pretty much all the time. If your java app can call a C library, then a C library is much more useful than a Java one, you instantly give access to it from every other language out there whereas a java one would only be accessed from other java apps.
Re:Lessons Learned 20 Years Ago at JPL/Nasa (Score:3, Insightful)
Yes, there's more than back-prop for succesfull neural processing. One of the most instereseting approaches IMO were done by Liaw and Berger [ieee.org] on adaptable sinaptic training models, but that was more than ten years ago!