Sakib1263/VGG-1D-2D-Tensorflow-Keras
Models Supported: VGG11, VGG13, VGG16, VGG16_v2, VGG19 (1D and 2D versions with DEMO for Classification and Regression).
This provides pre-built VGG neural network models for classifying or predicting outcomes from various types of data. You can input one-dimensional data like time-series signals or two-dimensional data such as images, and it outputs a classification label or a predicted value. This is intended for machine learning practitioners or researchers who need to quickly set up and experiment with VGG architectures for their specific datasets.
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Use this if you need to apply established VGG deep learning models to your 1D or 2D datasets for classification or regression tasks.
Not ideal if you are looking for advanced, state-of-the-art models beyond the VGG architecture or prefer to build models from scratch.
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MIT
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Last pushed
Nov 25, 2021
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