Multi‐channel Sliced Deep RCNN with Residual Network for Text Classification: Influence Statistics

Expert Impact

Concepts for which they have has direct influence: Residual network , Convolutional neural .

Key People For Residual Network

Top KOLs in the world
#1
Kaiming He
focal loss object detection semantic segmentation
#2
Jian Sun
paint selection salient object video stabilization
#3
Shaoqing Ren
identity mappings local binary features random forest
#4
Xiangyu Zhang
identity mappings spatial pyramid pooling object detection
#5
Ross B Girshick
object detection focal loss mask rcnn
#6
Xiaoou Tang
discriminant analysis image search pedestrian detection

Multi‐channel Sliced Deep RCNN with Residual Network for Text Classification

Abstract

. We 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 other features from sentences where other machine learning methods cannot. The experimental results indicate that our model outperforms the traditional methods.