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I want to do segmentation of video in real time (30 fps, 640х480).
Is it possible on a Core 2 Duo E8500?
Could you point to some library or algorithm that can do this?
Take a look at S. Paris, Edge-preserving smoothing and mean-shift segmentation of video streams, ECCV 2008.
In general, yes, there are some segmentation algorithms that are computationally efficient and are likely to operate at frame rate. Often you can use some optimization tricks to improve the efficiency of algorithms, so if you want to know about a specific task or algorithm you need to provide more details so we can help. I disagree with Abid Rahman K, OpenCV is not necessarily the best option.
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I am looking for the machine learning correct approach for predicting the lottery numbers, not the most accurate answer but at least we have some predicted output. I am implementing the regression based and neural network models for this. Is their any specific approach which follows this?
It is impossible. The lottery numbers are random - actually to be more specific, the system is chaotic. You would require the initial configuration (positions etc) to insane (possibly infinite) precision to be able to make any predictions. Basically, don't even try it.
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I'm trying to develop an application to classify music in to probably favorite or not probably favorite by training a Neural network from music which are already marked as favorite by user himself. I never done audio analysis before so I know almost nothing about it. To make this an accurate classification model what features do I need to include in my dataset of music.
eg:- decibel values , frequency values, length of the audio
thank you
Start by using the music feature extractors from Essentia. You can for instance use their commandline tool. This provides you with tons of low-level audio features (30+ types), as well rhythm (6+ feature types) and tonal (6+ features).
You can also do the same with the Python bindings.
Spectrograms are a useful technique for visualising the spectrum of frequencies of a sound and how they vary during a very short period of time. You can use a similar technique known as Mel-Frequency Cepstral Coefficients (MFCC) as features for the dataset.
You can use Librosa's mfcc() function which generates an MFCC from time series audio data to make the task a lot easier
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This might not be the right place for this to ask, but I am interested in artificial neural networks and want to learn more.
How do you design a network and train it on source code so it can come up with programs for, for example, easy number theory problems?
What's the general name of this research field?
This is a hugely interesting, and very hard, problem area. It will probably take you months to read enough to even understand how to attack the problem. Here's a few things that might help you get started, and they are more to show the problems you will face than to provide solutions:
http://karpathy.github.io/2015/05/21/rnn-effectiveness/
Then read this, and related papers:
https://arxiv.org/pdf/1410.5401v2.pdf
Next, you probably want to read the classic papers in program synthesis and generation at the parse tree/AST level (mostly out of MIT, I think, in the early 90s.)
Best of luck. This is not trivial.
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Hi i want to predict health level(High,medium,low) in leaf using image processing and data mining.So far i thought using extract colors from leaf using Bayes algorithm to predict healthy of leaf. and data mining part have completed now.but i need extra features for prediction.we only used orchid leaf.So i can't use vain structure.Can anyone help me to what are the other features can be extracted from leaf for identify health level of leaf.Any idea or comments help me to improve my project. Thanks
There are many possible approaches to a problem like this. One common method is the bag-of-features model. Take a look at this example using the Computer Vision System Toolbox in MATLAB.
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I wanna experiment k-means clustering method on different kind of images, so I am trying to find different kind of images used in image segmentation such as MRI images.I want to gather some more categories.
Any suggestion would be gratefully appreciated.
Although this is not the correct place for asking your question, to help you ,Image segmentation has a wide range of application including segmenting Satellite imagery
and Medical Imaging images, Texture Recognition, Facial Recognition System, Automatic Number Plate Recognition, and a lot of other machine vision applications.