The `keras.layers.TimeDistributed` class in Python's Keras library allows for the application of a specific layer to each temporal slice of an input tensor. This means that the layer is applied independently to every timestep input in the sequence. It is useful in tasks such as video processing, where each frame of a video can be treated separately. By wrapping a layer with `TimeDistributed`, the layer's parameters are shared across all timesteps, enabling the network to learn from the temporal dependencies within the sequence.
Python TimeDistributed - 37 examples found. These are the top rated real world Python examples of keras.layers.TimeDistributed extracted from open source projects. You can rate examples to help us improve the quality of examples.