RCNNText classificationBigramMultichannelDeep neural networkResidual networkWe propose a multi-channel sliced deep Recurrent convolutional neural network (RCNN) with a residual network.We expand the RCNN into a deep neural network.Our proposed model can directly learn to extract bigram features and ...
Multi-Channel Mask R-CNN was then used to classify and locate the defects. The experimental results show that the proposed method achieves a 98.70% overall classification accuracy and a 95.31% mean average precision, and only 2.5 s was needed to detect a batch of 50 standard images and 50 ...
Defect Detection of Industry Wood Veneer Based on NAS and Multi-Channel Mask R-CNN.doi:10.3390/S20164398Jiahao ShiZhenye LiTingting ZhuDongyi WangChao NiMultidisciplinary Digital Publishing Institute
However, using the conventional 3D CNNs to extract the spectral–spatial feature for HSIs results in too many parameters as HSIs have plenty of spatial redundancy. To address this issue, in this paper, we first design multiscale convolution to extract the contextual feature of different scales ...
Mental Health Sentiment Analysis Multi-channel CNN auto_awesome_motion View Active Events Uğur Atlı·4mo ago· 275 views arrow_drop_up0 Copy & Edit7 more_vert
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