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 ...
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 ...
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 ...
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
To tackle the small-scale characteristics of honeycomb lung lesions, we designed the MSCA-Sp R-CNN model, an instance segmentation framework that integrates a multi-scale channel attention module and a dual sub-pixel convolution upsampling module. Experimental results on the CC-CCII and UESTC-CO...