AIMC Topic: Attention

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Fast environmental sound classification based on resource adaptive convolutional neural network.

Scientific reports Apr 22, 2022
Recently, with the construction of smart city, the research on environmental sound classification (ESC) has attracted the attention of academia and industry. The development of convolutional neural network (CNN) makes the accuracy of ESC reach a high...
Neural Networks, Computer Sound Attention
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SCC-MPGCN: self-attention coherence clustering based on multi-pooling graph convolutional network for EEG emotion recognition.

Journal of neural engineering Apr 21, 2022
The emotion recognition with electroencephalography (EEG) has been widely studied using the deep learning methods, but the topology of EEG channels is rarely exploited completely. In this paper, we propose a self-attention coherence clustering based ...
Neural Networks, Computer Cluster Analysis Emotions Electroencephalography Attention
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Design of Sports Event Evaluation and Classification Method Based on Deep Neural Network.

Computational intelligence and neuroscience Apr 18, 2022
Large-scale sports events with high-level competition as the main content will have a great impact on the host city whether from the economic level or from the social level. With the improvement of human civilization, people realize that the holding ...
Humans Neural Networks, Computer Attention
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COVID Detection From Chest X-Ray Images Using Multi-Scale Attention.

IEEE journal of biomedical and health informatics Apr 14, 2022
Deep learning based methods have shown great promise in achieving accurate automatic detection of Coronavirus Disease (covid) - 19 from Chest X-Ray (cxr) images.However, incorporating explainability in these solutions remains relatively less explored...
Humans Neural Networks, Computer COVID-19 Algorithms SARS-CoV-2 Deep Learning Pneumonia Attention X-Rays
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iCatcher: A neural network approach for automated coding of young children's eye movements.

Infancy : the official journal of the International Society on Infant Studies Apr 13, 2022
Infants' looking behaviors are often used for measuring attention, real-time processing, and learning-often using low-resolution videos. Despite the ubiquity of gaze-related methods in developmental science, current analysis techniques usually involv...
Humans Neural Networks, Computer Learning Infant Eye Movements Child, Preschool Child Attention
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SE-BLTCNN: A channel attention adapted deep learning model based on PSSM for membrane protein classification.

Computational biology and chemistry Apr 6, 2022
Membrane protein classification is a key to inferring the function of uncharacterized membrane protein. To get around the time-consuming and expensive biochemical experiments in the wet lab, there has been a lot of research focusing on developing fas...
Neural Networks, Computer Deep Learning Membrane Proteins Attention Position-Specific Scoring Matrices
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MSAL-Net: improve accurate segmentation of nuclei in histopathology images by multiscale attention learning network.

BMC medical informatics and decision making Apr 4, 2022
BACKGROUND: The digital pathology images obtain the essential information about the patient's disease, and the automated nuclei segmentation results can help doctors make better decisions about diagnosing the disease. With the speedy advancement of c...
Humans Neural Networks, Computer Image Processing, Computer-Assisted Attention
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Predicting the Survival of Cancer Patients With Multimodal Graph Neural Network.

IEEE/ACM transactions on computational biology and bioinformatics Apr 1, 2022
In recent years, cancer patients survival prediction holds important significance for worldwide health problems, and has gained many researchers attention in medical information communities. Cancer patients survival prediction can be seen the classif...
Humans Neural Networks, Computer Neoplasms Proteins Attention
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Unbalanced Fault Diagnosis Based on an Invariant Temporal-Spatial Attention Fusion Network.

Computational intelligence and neuroscience Mar 30, 2022
The health status of mechanical bearings concerns the safety of equipment usage. Therefore, it is of crucial importance to monitor mechanical bearings. Currently, deep learning is the mainstream approach for this task. However, in practical situation...
Neural Networks, Computer Attention
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GHNN: Graph Harmonic Neural Networks for semi-supervised graph-level classification.

Neural networks : the official journal of the International Neural Network Society Mar 24, 2022
Graph classification aims to predict the property of the whole graph, which has attracted growing attention in the graph learning community. This problem has been extensively studied in the literature of both graph convolutional networks and graph ke...
Neural Networks, Computer Algorithms Learning Attention
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