AIMC Topic: Attention

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Using Eye Gaze to Enhance Generalization of Imitation Networks to Unseen Environments.

IEEE transactions on neural networks and learning systems
Vision-based autonomous driving through imitation learning mimics the behavior of human drivers by mapping driver view images to driving actions. This article shows that performance can be enhanced via the use of eye gaze. Previous research has shown...

Incorporation of residual attention modules into two neural networks for low-dose CT denoising.

Medical physics
PURPOSE: The low-dose computed tomography (CT) imaging can reduce the damage caused by x-ray radiation to the human body. However, low-dose CT images have a different degree of artifacts than conventional CT images, and their resolution is lower than...

Contrast-Attentive Thoracic Disease Recognition With Dual-Weighting Graph Reasoning.

IEEE transactions on medical imaging
Automatic thoracic disease diagnosis is a rising research topic in the medical imaging community, with many potential applications. However, the inconsistent appearances and high complexities of various lesions in chest X-rays currently hinder the de...

Transferable Multilevel Attention Neural Network for Accurate Prediction of Quantum Chemistry Properties via Multitask Learning.

Journal of chemical information and modeling
The development of efficient models for predicting specific properties through machine learning is of great importance for the innovation of chemistry and material science. However, predicting global electronic structure properties like Frontier mole...

Medical Image Classification Algorithm Based on Visual Attention Mechanism-MCNN.

Oxidative medicine and cellular longevity
Due to the complexity of medical images, traditional medical image classification methods have been unable to meet the actual application needs. In recent years, the rapid development of deep learning theory has provided a technical approach for solv...

Behavioral validation of novel high resolution attention decoding method from multi-units & local field potentials.

NeuroImage
The ability to access brain information in real-time is crucial both for a better understanding of cognitive functions and for the development of therapeutic applications based on brain-machine interfaces. Great success has been achieved in the field...

How Robots Help Nurses Focus on Professional Task Engagement and Reduce Nurses' Turnover Intention.

Journal of nursing scholarship : an official publication of Sigma Theta Tau International Honor Society of Nursing
PURPOSE: To examine how robot-enabled focus on professional task engagement and robot-reduced nonprofessional task engagement are related to nurses' professional turnover intention.

STAC: Spatial-Temporal Attention on Compensation Information for Activity Recognition in FPV.

Sensors (Basel, Switzerland)
Egocentric activity recognition in first-person video (FPV) requires fine-grained matching of the camera wearer's action and the objects being operated. The traditional method used for third-person action recognition does not suffice because of (1) t...

Attention-Guided Multi-Branch Convolutional Neural Network for Mitosis Detection From Histopathological Images.

IEEE journal of biomedical and health informatics
Mitotic count is an important indicator for assessing the invasiveness of breast cancers. Currently, the number of mitoses is manually counted by pathologists, which is both tedious and time-consuming. To address this situation, we propose a fast and...

Deep Coattention-Based Comparator for Relative Representation Learning in Person Re-Identification.

IEEE transactions on neural networks and learning systems
Person re-identification (re-ID) favors discriminative representations over unseen shots to recognize identities in disjoint camera views. Effective methods are developed via pair-wise similarity learning to detect a fixed set of region features, whi...