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MRI Classification with ConvNeXt & LSTM by Parsa Sinichi is a document available to read on EtoBox.
What is MRI Classification with ConvNeXt & LSTM about?
The document outlines a method for processing MRI slices using a ConvNeXt encoder followed by a bidirectional LSTM for classification. It details the architecture, including the LSTM configuration with two layers and 256 hidden units, and describes preprocessing steps such as resizing and data augmentation. The model is implemented in PyTorch, trained on Kaggle, and optimized with specific parameters over 25 epochs using cross-validation.
- Author
- Parsa Sinichi
- Language
- EN