OPTIMAL DATASET SELECTION FOR TRANSFERLEARNING
DOI:
https://doi.org/10.17770/het2021.25.6777Keywords:
datasets, Earth Mover’s Distance (EMD), ImageNet, neural networks, transfer learning,Abstract
The proposed article describes transfer learning and Earth Mover’s Distance (EMD) methodology application in machine learning. The goal was to find out the shortest distance among three datasets in order to identifyt dataset, which is more suited for neural network pretraining. The experiment was completed using Python programming language and Jupyter Notebook. Neural network pretrained on ImageNet dataset was applied as feature extractor. The extracted feature vectors of datasets were applied to calculate the minimal distance using EMD algorithm.Downloads
References
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Dataset “Plants_Dataset[99 classes]” by Muhammad jawad - https://www.kaggle.com/muhammadjawad1998/plants-dataset99-classes
Dataset “Animals-10” by Corrado Alessio - https://www.kaggle.com/alessiocorrado99/animals10
Dataset “Flowers Recognition” by Alexander Mamaev - https://www.kaggle.com/alxmamaev/flowers-recognition.
