Classifying images using Machine Learning or Deep Learning?
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I am pretty new to image processing and machine learning. Currently, I am doing a school project where I have to classify images in: bottle of water or can of soda. The idea is to train a model with different brands of bottles of water and cans of soda. Then, if one of those brands appear, classify the image in one of the two categories. Is this possible using the Matlab machine learning toolbox or the deep learning one? Any suggestion?
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First try the general machine learning algorithms to classify such as Support Vector Machines. The following example would be similar to what you want to do:
- Digit Classification Using HOG Features https://www.mathworks.com/help/vision/examples/digit-classification-using-hog-features.html
If you are not satisfied with your classification results, and you have a lot of image data, consider to use Deep Learning. The easiest way to get started is to use the pre-trained model such as alexnet:
- Pretrained Convolutional Neural Network https://www.mathworks.com/help/nnet/ug/install-trained-convolutional-deep-network.html
If you want to use more complex ones, see the examples in the documentation first.
1 个评论
Qazi Arbab Ahmed
2017-2-21
I have Trained my model using Statistical App. I am using 4 features Finally to train my Model. Now I have a test Data set that I have read, How can I test using my Trained model. I have exported my model into workspace but when I do test my Images it gives the following erroe.
yfit = trainedClassifier.predictFcn(I2) Error using array2table (line 28) X must be a 2-D matrix.
Error in mlearnapp.internal.model.DatasetSpecification>@(x)array2table(x,'VariableNames',this.PredictorNames)
Error in mlearnapp.internal.model.DatasetSpecification>@(x)exportableClassifier.predictFcn(predictorExtractionFcn(x)) (line 138) newExportableClassifier.predictFcn = @(x) exportableClassifier.predictFcn(predictorExtractionFcn(x));
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Khaoula Riahi
2019-3-18
0 个投票
how to install machine learning in Matlab version 2013?
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