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Andre Henriques 2023-12-18 21:33:53 +00:00
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main.bib
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@ -125,3 +125,10 @@ author={
note = {[Online; accessed 18. Dec. 2023]},
url = {https://docs.aws.amazon.com/rekognition/latest/customlabels-dg/what-is.html?pg=ln&sec=ft}
}
@misc{amazon-rekognition-custom-labels-training,
title = {{Training an Amazon Rekognition Custom Labels model - Rekognition}},
year = {2023},
month = dec,
note = {[Online; accessed 18. Dec. 2023]},
url = {https://docs.aws.amazon.com/rekognition/latest/customlabels-dg/training-model.html#tm-console}
}

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report/report.tex
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@ -91,7 +91,11 @@
%Amazon provides bespoque machine learning services that if were contacted would be able to provide image classification services. Amazon provides general machine learning services \cite{amazon-machine-learning}.
Amazon provides an image classification service called rekognition \cite{amazon-rekognition}. This services provides multiple services from face regonition, celebrity regonition, object regonition and others. One of this services is called custom labels \cite{amazon-rekognition-custom-labels} which provides the most similiar service, to the one this project is about. The custom labels service allows the users to provide custom datasets and labels and using AutoML the rekognition service would generate a model that allows the users to classify images acording to the generated model.
Amazon provides an image classification service called rekognition \cite{amazon-rekognition}. This services provides multiple services from face regonition, celebrity regonition, object regonition and others. One of this services is called custom labels \cite{amazon-rekognition-custom-labels} which provides the most similiar service, to the one this project is about. The custom labels service allows the users to provide custom datasets and labels and using AutoML the rekognition service would generate a model that allows the users to classify images acording to the generated model.
The models generated using Amazon's rekognition dont provide ways to update the number of labels that were originaly created without generating a new project which will envolve retraining a large part of the model which would envolve large downtime between being able to add new classes. Training models also could take 30 minutes to 24 hours \cite{amazon-rekognition-custom-labels-training} which cloud result in up to 24 hours of lag between the need of creating a new label and beeing able to classify that label. A problem also arrises when the uses needs to add more than one label at the same time, for example the user sees the need to create a new label and starts a new model training, but while the model is traning a new label is also needed the user now either stops the training of the new model and retrains a new one or waits until the one currently running stops and trains a new one. This is not very efficient.
%https://aws.amazon.com/machine-learning/ml-use-cases/