WiMi Hologram Cloud announces proposed hybrid recurrent neural network

WiMi Hologram Cloud proposed hybrid recurrent neural network architecture-based human-robot collaboration intent recognition. Hybrid recurrent neural network architecture is a model that combines recurrent neural network and convolutional neural network. RNN is a neural network suitable for modeling and sequential data processing, which can efficiently capture temporal information and contextual relationships in the data through recurrent connections and hidden state updating, it can effectively capture temporal information and contextual relationships in sequence data. CNN can effectively extract data features. Hybrid recurrent neural network combines the advantages of RNN and CNN, which can better capture sequence information and local features, and can better handle intention recognition for human-robot collaboration. In hybrid recurrent neural network architecture, the input data is first subjected to feature extraction by CNN, then temporal modeling by recurrent layer, and then mapping the features to the intent by a fully connected layer. During the training process, the backpropagation algorithm is used to optimize the model parameters to improve the accuracy of intent recognition.