...), convolutional neural networks (CNN) and an attention mechanism, resulting in the Bidirectional Gated Recurrent Units Convolution Attention (BiGRU-CNN-AT) model. The BiGRU captures potential semantic features, the CNN extracts local features and the attention mechanism identifies keywords critical...

... scenarios. Therefore, the authors proposed to improve the transfer efficiency of the model for new scenarios through transfer learning. Design/methodology/approach First, the authors achieved multi-task autonomous driving by training a model combining convolutional neural network and different...

... objective of the work is to reduce the false positive rate during the classification. Design/methodology/approach In this work, a hybrid method using convolutional neural networks (CNNs), extreme gradient boosting (XGBoost) and long-short-term memory networks (LSTMs) has been proposed to distinguish...

... of the chair, and image data of the postu.re were collected. A total of 26 children participated in the experiment and collected image data for a total of seven postures. The authors used convolutional neural networks (CNN) algorithm consisting of seven layers. In addition, to compare the accuracy...