Convolutional neural networkSentiment informationThe sentence-level sentiment classification is a classic topic of natural language processing, which aims to decide the sentiment\ntendency toward a sentence. However, previous studies ignore the significant role of words with sentimental tendencies in\n...
Convolutional Neural NetworksInputs channelsEnsemble classificationIn this paper, we propose an ensemble classification approach to the Pedestrian Detection (PD) problem, resorting to distinct input channels and Convolutional Neural Networks (CNN). This methodology......
Deep learning with convolutional neural networks (deep ConvNets) has revolutionized computer vision through end-to-end learning, i.e. learning from the raw data. Now, there is increasing interest in using deep ConvNets for end-to-end EEG analysis. However, little is known about many important...
2 Related Work 随着面向方面的情感分析的蓬勃发展,目前的研究大致可分为三类:基于注意的神经模型(Attention-Based Neural Networks)、基于句法规则的神经网络(Syntactic-Based Recurrent Neural Networks)和基于句法的图神经网络(Syntactic-Based Graph Neural Networks)。我们的工作是基于这些最近的大量努力。 基于语法的图...
Presently, how to utilize Graph Neural Networks(GNN) to fuse syntactic and semantic features still deserves further research. A multi-channel enhanced graph convolutional network model is proposed in this paper to address the above issues. First, graph convolution operations on syntactic graphs ...
Panotti: A Convolutional Neural Network classifier for multichannel audio waveforms (Image of large-eared Panotti people, Wikipedia) This is a version of theaudio-classifier-keras-cnnrepo (which is a hack of@keunwoochoi's compact_cnn code). Difference with Panotti is, it has been generalized...
To improve the accuracy of human activity recognition (HAR) based on body area network (BAN), a novel spatio-temporal network combining multi-channel convolutional neural network (CNN) with graph convolutional neural network (GCN) is proposed in this paper. Based on BAN including multi-sensors, ...
In this article, we propose a method based on multi-task CNN to achieve compression and reconstruction of channel state information through a multi-scale and multi-channel convolutional neural network. We also introduce a dynamic learning rate model to improve the accuracy of channel state ...
In this paper, novel early and late fusion convolutional neural networks (CNNs) are proposed for multi-channel speech enhancement. Two beamformers namely delay-and-sum and minimum variance distortionless response are used as prefilters to suppress the effect of noise in the input microphone array...
Salient object detection is a hot spot of current computer vision. The emergence of the convolutional neural network (CNN) greatly improves the existing de