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Recurrent convolutional neural network for video classification
2016 IEEE International Conference on Multimedia and Expo (ICME), 2016Video classification is more difficult than image classification since additional motion feature between image frames and amount of redundancy in videos should be taken into account. In this work, we proposed a new deep learning architecture called recurrent convolutional neural network (RCNN) which combines convolution operation and recurrent links ...
Zhenqi Xu, Jiani Hu, Weihong Deng
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Convolutional and Recurrent Neural Networks
2018In the previous chapters, you have looked at fully connected networks and all the problems encountered while training them. The network architecture we have used, one in which each neuron in a layer is connected to all neurons in the previous and following layer, is not really good at many fundamental tasks, such as image recognition, speech ...
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Convolutional recurrent neural network for question answering
2017 3rd International Conference on Electrical Information and Communication Technology (EICT), 2017Question answering has become a very important task for natural language understanding as most natural language processing problems can be posed as a question answering problem. Recurrent neural network (RNN) is a standard baseline model for various sequence prediction tasks including question answering.
M. M. Arefin Zaman, Sadia Zaman Mishu
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Convolutional Recurrent Neural Networks for Computer Network Analysis
2019The paper proposes a method of computer network user detection with recurrent neural networks. We use long short-term memory and gated recurrent unit neural networks. To present URLs from computer network sessions to the neural networks, we add convolutional input layers. Moreover, we transform requested URLs by one-hot character-level encoding.
Jakub Nowak +2 more
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Intrusion Detection Using Convolutional Recurrent Neural Network
Proceedings of the 2019 8th International Conference on Computing and Pattern Recognition, 2019There are two main problems in the current abnormal network traffic monitoring methods: feature dependence and low accuracy. To solve these problems, we propose a novel deep learning model OCL based on network traffic in this paper. Our OCL model consists of one-dimensional convolutional neural network and long short-term memory.
Tongtong Su, Huazhi Sun, Sheng Wang
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Recurrent Convolutional Neural Networks for Text Classification
Proceedings of the AAAI Conference on Artificial Intelligence, 2015Text classification is a foundational task in many NLP applications. Traditional text classifiers often rely on many human-designed features, such as dictionaries, knowledge bases and special tree kernels. In contrast to traditional methods, we introduce a recurrent convolutional neural network for text classification without human ...
Siwei Lai, Liheng Xu, Kang Liu, Jun Zhao
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Convolutional Recurrent Neural Networks for Text Classification
2019 International Joint Conference on Neural Networks (IJCNN), 2019Text classification is an important task in natural language processing with wide applications. Traditional text classification methods manually extract the features which are later fed into the classifier for training. Recent researchers have employed convolutional neural networks or recurrent neural networks for text classification motivated by the ...
Ruishuang Wang +4 more
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Recurrent convolutional neural network for speech processing
2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2017Different neural networks have exhibited excellent performance on various speech processing tasks, and they usually have specific advantages and disadvantages. We propose to use a recently developed deep learning model, recurrent convolutional neural network (RCNN), for speech processing, which inherits some merits of recurrent neural network (RNN) and
Yue Zhao, Xingyu Jin, Xiaolin Hu
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Direction Finding Using Convolutional Neural Networks and Convolutional Recurrent Neural Networks
2020 28th Signal Processing and Communications Applications Conference (SIU), 2020Fehmi Ayberk Uçkun +3 more
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