Results 11 to 20 of about 9,795 (189)
JMIR Medical Informatics, 2022 BackgroundIt is hard to distinguish cerebral aneurysms from overlapping vessels in 2D digital subtraction angiography (DSA) images due to these images’ lack of spatial information.
JunHua Liao +6 more
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Attention Neural Network for Biomedical Word Sense Disambiguation
Discrete Dynamics in Nature and Society, 2022 In order to improve the disambiguation accuracy of biomedical words, this paper proposes a disambiguation method based on the attention neural network. The biomedical word is viewed as the center. Morphology, part of speech, and semantic information from
Chun-Xiang Zhang +4 more
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Network evasion detection with Bi-LSTM model [PDF]
Journal of Physics: Conference Series, 2019 4 pages,5 ...
Kehua Chen, Jingping Jia
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A Bidirectional Long Short-Term Memory Model Algorithm for Predicting COVID-19 in Gulf Countries
Life, 2021 Accurate prediction models have become the first goal for aiding pandemic-related decisions. Modeling and predicting the number of new active cases and deaths are important steps for anticipating and controlling COVID-19 outbreaks.
Theyazn H. H. Aldhyani, Hasan Alkahtani
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A ConvBiLSTM Deep Learning Model-Based Approach for Twitter Sentiment Classification
IEEE Access, 2021 Being one of the most widely used social media tools, Twitter is seen as an important source of information for acquiring people’s attitudes, emotions, views and feedbacks.
Sakirin Tam +2 more
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Smart Contract Classification With a Bi-LSTM Based Approach [PDF]
IEEE Access, 2020 With the number of smart contracts growing rapidly, retrieving the relevant smart contracts quickly and accurately has become an important issue. A key step for recognizing the related smart contracts is able to classify them accurately. Different from traditional text, the smart contract is composed of several parts: source code, code comments and ...
Gang Tian +5 more
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GAN‐LSTM‐3D: An efficient method for lung tumour 3D reconstruction enhanced by attention‐based LSTM
CAAI Transactions on Intelligence Technology, EarlyView., 2023 Abstract Three‐dimensional (3D) image reconstruction of tumours can visualise their structures with precision and high resolution. In this article, GAN‐LSTM‐3D method is proposed for 3D reconstruction of lung cancer tumours from 2D CT images. Our method consists of three phases: lung segmentation, tumour segmentation, and tumour 3D reconstruction. Lung
Lu Hong +12 more
wiley +1 more source
CoRR, 2017 Recurrent neural networks like long short-term memory (LSTM) are important architectures for sequential prediction tasks. LSTMs (and RNNs in general) model sequences along the forward time direction. Bidirectional LSTMs (Bi-LSTMs) on the other hand model sequences along both forward and backward directions and are generally known to perform better at ...
Samira Shabanian +3 more
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Attention Based Graph Bi-LSTM Networks for Traffic Forecasting [PDF]
2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC), 2020 Traffic forecasting is of great importance to vehicle routing, traffic signal control and urban planning. However, traffic forecasting task is challenging due to several factors, such as complex spatial topological structure and dynamic changing of traffic status.
Han Zhao +4 more
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Sensors, 2023 The excretion care robot’s (ECR) accurate recognition of transfer-assisted actions is crucial during its usage. However, transfer action recognition is a challenging task, especially since the differentiation of actions seriously affects its recognition ...
Yina Wang +4 more
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