Custom keras layers for hyperspectral data and RNNs
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Updated
Jun 25, 2024 - Python
Custom keras layers for hyperspectral data and RNNs
Implementations for a family of attention mechanisms, suitable for all kinds of natural language processing tasks and compatible with TensorFlow 2.0 and Keras.
K-CAI NEURAL API - Keras based neural network API that will allow you to create parameter-efficient, memory-efficient, flops-efficient multipath models with new layer types. There are plenty of examples and documentation.
Keras Core Addons: Useful extra functionality for Keras Core.
Utilities for Keras - Deep Learning library
Seq2Seq model that restores punctuation on English input text.
transform sets of bezier curves into a raster image
Keras, Tensorflow eager execution layers for exponential smoothing
Utility for extracting layer weights and biases from Keras models
My first Python repo with codes in Machine Learning, NLP and Deep Learning with Keras and Theano
A Keras layer that performs a map operation over a ragged tensor
用tensorflow2實現weight standardization,為了訓練方便將其建立成keras layer。
Keras Custom Layers of AdaCos and ArcFace contains experiments in caltech birds 2011(CUB-200-2011).
A collection of layers, ops, utilities and more for TensorFlow 2.0 high-level API Keras
Keras implementation of Phased LSTM [https://arxiv.org/abs/1610.09513]
CRF(Conditional Random Field) Layer for TensorFlow 1.X with many powerful functions
A Keras layer that acts as multiplexer for Dense layers (Tensorflow backend only)
A detailed Research project on Character-Segmentation using Neural Networks!
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