Results 1 to 10 of about 22,978 (161)
EleAtt-RNN: Adding Attentiveness to Neurons in Recurrent Neural Networks [PDF]
IEEE Transactions on Image Processing, 2020 IEEE Transactions on Image Processing (Accept).
Pengfei Zhang +2 more
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MV-RNN: A Multi-View Recurrent Neural Network for Sequential Recommendation [PDF]
IEEE Transactions on Knowledge and Data Engineering, 2020 Sequential recommendation is a fundamental task for network applications, and it usually suffers from the item cold start problem due to the insufficiency of user feedbacks. There are currently three kinds of popular approaches which are respectively based on matrix factorization (MF) of collaborative filtering, Markov chain (MC), and recurrent neural ...
Qiang Cui, Shu Wu, Qiang Liu
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Fundamentals of Recurrent Neural Network (RNN) and Long Short-Term Memory (LSTM) network [PDF]
Physica D: Nonlinear Phenomena, 2020 43 pages, 10 figures, 78 ...
Alex Sherstinsky
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RNN-Test: Towards Adversarial Testing for Recurrent Neural Network Systems [PDF]
IEEE Transactions on Software Engineering, 2022 While massive efforts have been investigated in adversarial testing of convolutional neural networks (CNN), testing for recurrent neural networks (RNN) is still limited and leaves threats for vast sequential application domains. In this paper, we propose an adversarial testing framework RNN-Test for RNN systems, focusing on sequence-to-sequence ...
Jianmin Guo, Heyuan Shi, Yu Jiang
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Comparative effectiveness of convolutional neural network (CNN) and recurrent neural network (RNN) architectures for radiology text report classification [PDF]
Artificial Intelligence in Medicine, 2019 Sadid A Hasan +2 more
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Energy Consumption Prediction of Office Buildings Based on CNN-RNN Combined Model
Shanghai Jiaotong Daxue xuebao, 2022 In order to accurately reflect the operation characteristics of office buildings, a convolutional neural network(CNN)-recurrent neural network(RNN)combined model for energy consumption prediction of office buildings is proposed by using the good feature ...
ZENG Guozhi, WEI Ziqing, YUE Bao, DING Yunxiao, ZHENG Chunyuan, ZHAI Xiaoqiang
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Measurement: Sensors, 2023 This proposed model introduces novel deep learning methodologies. The objective here is to create a reliable intrusion detection mechanism to help identify malicious attacks.
Arun Kumar Silivery +4 more
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IEEE Access, 2021 The attention-based SeriesNet (A-SeriesNet) combined augmented attention residual learning module-based convolutional neural network (augmented ARLM-CNN) subnetwork with hidden state attention module-based recurrent neural network (HSAM-RNN) subnetwork ...
Yepeng Cheng, Yasuhiko Morimoto
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IEEE Access, 2022 Landslide risk assessment is an important component of the landslide research field. For the problem of landslide assessment indicators, we utilize the TOPSIS-Entropy method to assess the risk situation of landslide occurrences, which is easy to obtain ...
Di Zhang +5 more
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Recurrent neural network from adder’s perspective: Carry-lookahead RNN [PDF]
Neural Networks, 2021 The recurrent network architecture is a widely used model in sequence modeling, but its serial dependency hinders the computation parallelization, which makes the operation inefficient. The same problem was encountered in serial adder at the early stage of digital electronics. In this paper, we discuss the similarities between recurrent neural network (
Haowei Jiang +4 more
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