AIMC Topic: Attention

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Multi-task learning for Chinese clinical named entity recognition with external knowledge.

BMC medical informatics and decision making Dec 31, 2021
BACKGROUND: Named entity recognition (NER) on Chinese electronic medical/healthcare records has attracted significantly attentions as it can be applied to building applications to understand these records. Most previous methods have been purely data-...
Neural Networks, Computer Electronic Health Records Humans Attention Names China
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Attention Autoencoder for Generative Latent Representational Learning in Anomaly Detection.

Sensors (Basel, Switzerland) Dec 24, 2021
Today, accurate and automated abnormality diagnosis and identification have become of paramount importance as they are involved in many critical and life-saving scenarios. To accomplish such frontiers, we propose three artificial intelligence models ...
Electrocardiography Attention Algorithms Normal Distribution Artificial Intelligence Humans
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A Multi-RNN Research Topic Prediction Model Based on Spatial Attention and Semantic Consistency-Based Scientific Influence Modeling.

Computational intelligence and neuroscience Dec 18, 2021
Computer science discipline includes many research fields, which mutually influence and promote each other's development. This poses two great challenges of predicting the research topics of each research field. One is how to model fine-grained topic...
Learning Attention Neural Networks, Computer Models, Theoretical Semantics
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Posture Detection of Individual Pigs Based on Lightweight Convolution Neural Networks and Efficient Channel-Wise Attention.

Sensors (Basel, Switzerland) Dec 15, 2021
In this paper, a lightweight channel-wise attention model is proposed for the real-time detection of five representative pig postures: standing, lying on the belly, lying on the side, sitting, and mounting. An optimized compressed block with symmetri...
Attention Neural Networks, Computer Sitting Position Posture Swine Animals
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Deep Learning Based on Hierarchical Self-Attention for Finance Distress Prediction Incorporating Text.

Computational intelligence and neuroscience Dec 10, 2021
To detect comprehensive clues and provide more accurate forecasting in the early stage of financial distress, in addition to financial indicators, digitalization of lengthy but indispensable textual disclosure, such as Management Discussion and Analy...
Attention Deep Learning
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Deep semi-supervised learning via dynamic anchor graph embedding in latent space.

Neural networks : the official journal of the International Neural Network Society Dec 1, 2021
Recently, deep semi-supervised graph embedding learning has drawn much attention for its appealing performance on the data with a pre-specified graph structure, which could be predefined or empirically constructed based on given data samples. However...
Algorithms Supervised Machine Learning Neural Networks, Computer Attention
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Noise Conscious Training of Non Local Neural Network Powered by Self Attentive Spectral Normalized Markovian Patch GAN for Low Dose CT Denoising.

IEEE transactions on medical imaging Nov 30, 2021
The explosive rise of the use of Computer tomography (CT) imaging in medical practice has heightened public concern over the patient's associated radiation dose. On the other hand, reducing the radiation dose leads to increased noise and artifacts, w...
Signal-To-Noise Ratio Image Processing, Computer-Assisted Attention Tomography, X-Ray Computed Neural Networks, Computer Computers Humans Algorithms
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DCACNet: Dual context aggregation and attention-guided cross deconvolution network for medical image segmentation.

Computer methods and programs in biomedicine Nov 29, 2021
BACKGROUND AND OBJECTIVE: Segmentation is a key step in biomedical image analysis tasks. Recently, convolutional neural networks (CNNs) have been increasingly applied in the field of medical image processing; however, standard models still have some ...
Neural Networks, Computer Image Processing, Computer-Assisted Data Collection Attention
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Physics-based learning with channel attention for Fourier ptychographic microscopy.

Journal of biophotonics Nov 28, 2021
Fourier ptychographic microscopy (FPM) is a computational imaging technology for large field-of-view, high resolution and quantitative phase imaging. In FPM, low-resolution intensity images captured with angle-varying illumination are synthesized in ...
Lighting Neural Networks, Computer Microscopy Attention Fourier Analysis
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Learning Spatial-Spectral-Temporal EEG Representations with Deep Attentive-Recurrent-Convolutional Neural Networks for Pain Intensity Assessment.

Neuroscience Nov 26, 2021
Electroencephalogram (EEG)-based quantitative pain measurement is valuable in the field of clinical pain treatment, providing objective pain intensity assessment especially for nonverbal patients who are unable to self-report. At present, a key chall...
Attention Humans Pain Measurement Neural Networks, Computer Electroencephalography
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