AIMC Topic: Attention

Clear Filters Showing 341 to 350 of 574 articles

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 Feb 10, 2021
PURPOSE: To examine how robot-enabled focus on professional task engagement and robot-reduced nonprofessional task engagement are related to nurses' professional turnover intention.
Male Middle Aged Taiwan Young Adult Adult Nursing Staff, Hospital Personnel Turnover Robotics Attention Intention Humans Female
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STAC: Spatial-Temporal Attention on Compensation Information for Activity Recognition in FPV.

Sensors (Basel, Switzerland) Feb 5, 2021
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...
Humans Motion Attention Neural Networks, Computer Image Processing, Computer-Assisted
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Attention-Guided Multi-Branch Convolutional Neural Network for Mitosis Detection From Histopathological Images.

IEEE journal of biomedical and health informatics Feb 5, 2021
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...
Neural Networks, Computer Female Breast Neoplasms Attention Humans Mitosis
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Deep Coattention-Based Comparator for Relative Representation Learning in Person Re-Identification.

IEEE transactions on neural networks and learning systems Feb 4, 2021
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...
Algorithms Databases, Factual Reproducibility of Results Neural Networks, Computer Artificial Intelligence Software Attention Automated Facial Recognition Biometric Identification Deep Learning Image Processing, Computer-Assisted Benchmarking Humans
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Liver segmentation in abdominal CT images via auto-context neural network and self-supervised contour attention.

Artificial intelligence in medicine Jan 23, 2021
OBJECTIVE: Accurate image segmentation of the liver is a challenging problem owing to its large shape variability and unclear boundaries. Although the applications of fully convolutional neural networks (CNNs) have shown groundbreaking results, limit...
Image Processing, Computer-Assisted Neural Networks, Computer Liver Tomography, X-Ray Computed Attention
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Human papilloma virus detection in oropharyngeal carcinomas with in situ hybridisation using hand crafted morphological features and deep central attention residual networks.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Jan 22, 2021
Human Papilloma Virus (HPV) is a major risk factor for the development of oropharyngeal cancer. Automatic detection of HPV in digitized pathology tissues using in situ hybridisation (ISH) is a difficult task due to the variability and complexity of s...
Alphapapillomavirus Humans Deep Learning Attention Carcinoma Papillomaviridae Oropharyngeal Neoplasms
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Central Attention and a Dual Path Convolutional Neural Network in Real-World Tree Species Recognition.

International journal of environmental research and public health Jan 22, 2021
Identifying plants is not only the job of professionals, but also useful or essential for the plant lover and the general public. Although deep learning approaches for plant recognition are promising, driven by the success of convolutional neural net...
Databases, Factual Trees Neural Networks, Computer Recognition, Psychology Attention
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Preictal state detection using prodromal symptoms: A machine learning approach.

Epilepsia Jan 19, 2021
A reliable identification of a high-risk state for upcoming seizures may allow for preemptive treatment and improve the quality of patients' lives. We evaluated the ability of prodromal symptoms to predict preictal states using a machine learning (ML...
Vision Disorders Noise Area Under Curve Drug Resistant Epilepsy Speech Electroencephalography Female Prodromal Symptoms Surveys and Questionnaires Seizures Young Adult Humans Photophobia Support Vector Machine Attention Comprehension Adult Video Recording Machine Learning Male Hearing Loss Middle Aged Tinnitus Reading Affect
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Few-Shot Human-Object Interaction Recognition With Semantic-Guided Attentive Prototypes Network.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society Jan 11, 2021
Extreme instance imbalance among categories and combinatorial explosion make the recognition of Human-Object Interaction (HOI) a challenging task. Few studies have addressed both challenges directly. Motivated by the success of few-shot learning that...
Image Processing, Computer-Assisted Attention Semantics Pattern Recognition, Automated Humans Machine Learning Animals
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Automatic Lung Segmentation on Chest X-rays Using Self-Attention Deep Neural Network.

Sensors (Basel, Switzerland) Jan 7, 2021
Accurate identification of the boundaries of organs or abnormal objects (e.g., tumors) in medical images is important in surgical planning and in the diagnosis and prognosis of diseases. In this study, we propose a deep learning-based method to segme...
Neural Networks, Computer Attention Lung X-Rays Image Processing, Computer-Assisted
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