AIMC Topic: Attention

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Decoding Brain Representations by Multimodal Learning of Neural Activity and Visual Features.

IEEE transactions on pattern analysis and machine intelligence Oct 1, 2021
This work presents a novel method of exploring human brain-visual representations, with a view towards replicating these processes in machines. The core idea is to learn plausible computational and biological representations by correlating human neur...
Humans Brain Attention Visual Perception Neural Networks, Computer Algorithms
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Extended-Range Prediction Model Using NSGA-III Optimized RNN-GRU-LSTM for Driver Stress and Drowsiness.

Sensors (Basel, Switzerland) Sep 25, 2021
Road traffic accidents have been listed in the top 10 global causes of death for many decades. Traditional measures such as education and legislation have contributed to limited improvements in terms of reducing accidents due to people driving in und...
Algorithms Forecasting Attention Humans Neural Networks, Computer
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Medical Text Classification Using Hybrid Deep Learning Models with Multihead Attention.

Computational intelligence and neuroscience Sep 23, 2021
To unlock information present in clinical description, automatic medical text classification is highly useful in the arena of natural language processing (NLP). For medical text classification tasks, machine learning techniques seem to be quite effec...
Natural Language Processing Humans Machine Learning Neural Networks, Computer Attention Deep Learning
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Advances in bacterial concentration methods and their integration in portable detection platforms: A review.

Analytica chimica acta Sep 18, 2021
Early detection and identification of microbial contaminants is crucial in many sectors, including clinical diagnostics, food quality control and environmental monitoring. Biosensors have recently gained attention among other bacterial detection tech...
Microfluidics Attention Centrifugation Biosensing Techniques Bacteria
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Cross-species behavior analysis with attention-based domain-adversarial deep neural networks.

Nature communications Sep 17, 2021
Since the variables inherent to various diseases cannot be controlled directly in humans, behavioral dysfunctions have been examined in model organisms, leading to better understanding their underlying mechanisms. However, because the spatial and tem...
Caenorhabditis elegans Dopaminergic Neurons Mice, Inbred C57BL Dopamine Species Specificity Coleoptera Parkinson Disease Animals Humans Behavior, Animal Attention Mice Neural Networks, Computer
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A category attention instance segmentation network for four cardiac chambers segmentation in fetal echocardiography.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Sep 16, 2021
Fetal echocardiography is an essential and comprehensive examination technique for the detection of fetal heart anomalies. Accurate cardiac chambers segmentation can assist cardiologists to analyze cardiac morphology and facilitate heart disease diag...
Heart Ventricles Attention Image Processing, Computer-Assisted Heart Neural Networks, Computer Echocardiography
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Comparing Class-Aware and Pairwise Loss Functions for Deep Metric Learning in Wildlife Re-Identification.

Sensors (Basel, Switzerland) Sep 12, 2021
Similarity learning using deep convolutional neural networks has been applied extensively in solving computer vision problems. This attraction is supported by its success in one-shot and zero-shot classification applications. The advances in similari...
Animals, Wild Attention Awareness Neural Networks, Computer Animals
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Stimuli-Aware Visual Emotion Analysis.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society Sep 1, 2021
Visual emotion analysis (VEA) has attracted great attention recently, due to the increasing tendency of expressing and understanding emotions through images on social networks. Different from traditional vision tasks, VEA is inherently more challengi...
Humans Neural Networks, Computer Attention Algorithms Emotions
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Dual Attention Multi-Instance Deep Learning for Alzheimer's Disease Diagnosis With Structural MRI.

IEEE transactions on medical imaging Aug 31, 2021
Structural magnetic resonance imaging (sMRI) is widely used for the brain neurological disease diagnosis, which could reflect the variations of brain. However, due to the local brain atrophy, only a few regions in sMRI scans have obvious structural c...
Attention Magnetic Resonance Imaging Alzheimer Disease Deep Learning Cognitive Dysfunction Humans Brain
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Generative Adversarial Networks-Based Data Augmentation for Brain-Computer Interface.

IEEE transactions on neural networks and learning systems Aug 31, 2021
The performance of a classifier in a brain-computer interface (BCI) system is highly dependent on the quality and quantity of training data. Typically, the training data are collected in a laboratory where the users perform tasks in a controlled envi...
Brain-Computer Interfaces Imagination Humans Male Reproducibility of Results Machine Learning Computer Simulation Healthy Volunteers Electroencephalography Neural Networks, Computer Female Young Adult Psychomotor Performance Algorithms Adult Attention
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