AIMC Topic: Head

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Improving the Head Pose Variation Problem in Face Recognition for Mobile Robots.

Sensors (Basel, Switzerland) Jan 19, 2021
Face recognition is a technology with great potential in the field of robotics, due to its prominent role in human-robot interaction (HRI). This interaction is a keystone for the successful deployment of robots in areas requiring a customized assista...
Head Facial Recognition Robotics Face Humans Neural Networks, Computer
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Generation of Brain Dual-Energy CT from Single-Energy CT Using Deep Learning.

Journal of digital imaging Jan 11, 2021
Deep learning (DL) has shown great potential in conversions between various imaging modalities. Similarly, DL can be applied to synthesize a high-kV computed tomography (CT) image from its corresponding low-kV CT image. This indicates the feasibility...
Humans Deep Learning Head Signal-To-Noise Ratio Brain Tomography, X-Ray Computed
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Performance Analysis of a Head and Eye Motion-Based Control Interface for Assistive Robots.

Sensors (Basel, Switzerland) Dec 14, 2020
Assistive robots support people with limited mobility in their everyday life activities and work. However, most of the assistive systems and technologies for supporting eating and drinking require a residual mobility in arms or hands. For people with...
Motion Head Robotics Quadriplegia Hand Humans Eye Movements
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Hier R-CNN: Instance-Level Human Parts Detection and A New Benchmark.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society Nov 18, 2020
Detecting human parts at instance-level is an essential prerequisite for the analysis of human keypoints, actions, and attributes. Nonetheless, there is a lack of a large-scale, rich-annotated dataset for human parts detection. We fill in the gap by ...
Algorithms Databases, Factual Humans Neural Networks, Computer Benchmarking Head Foot Image Processing, Computer-Assisted Hand
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A fast and fully-automated deep-learning approach for accurate hemorrhage segmentation and volume quantification in non-contrast whole-head CT.

Scientific reports Nov 9, 2020
This project aimed to develop and evaluate a fast and fully-automated deep-learning method applying convolutional neural networks with deep supervision (CNN-DS) for accurate hematoma segmentation and volume quantification in computed tomography (CT) ...
Male Middle Aged Head Intracranial Hemorrhages Deep Learning Female Aged Humans Tomography, X-Ray Computed
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Comparison of Supervised and Unsupervised Deep Learning Methods for Medical Image Synthesis between Computed Tomography and Magnetic Resonance Images.

BioMed research international Nov 5, 2020
Cross-modality medical image synthesis between magnetic resonance (MR) images and computed tomography (CT) images has attracted increasing attention in many medical imaging area. Many deep learning methods have been used to generate pseudo-MR/CT imag...
Magnetic Resonance Imaging Multimodal Imaging Deep Learning Head Humans Image Processing, Computer-Assisted Tomography, X-Ray Computed
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Lightweight and Resource-Constrained Learning Network for Face Recognition with Performance Optimization.

Sensors (Basel, Switzerland) Oct 27, 2020
Despite considerable progress in face recognition technology in recent years, deep learning (DL) and convolutional neural networks (CNN) have revealed commendable recognition effects with the advent of artificial intelligence and big data. FaceNet wa...
Artificial Intelligence Algorithms Automated Facial Recognition Head Humans Deep Learning Neural Networks, Computer
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Combining deep learning with 3D stereophotogrammetry for craniosynostosis diagnosis.

Scientific reports Sep 18, 2020
Craniosynostosis is a condition in which cranial sutures fuse prematurely, causing problems in normal brain and skull growth in infants. To limit the extent of cosmetic and functional problems, swift diagnosis is needed. The goal of this study is to ...
Photogrammetry Head Craniosynostoses Facial Bones Case-Control Studies Humans Deep Learning Infant Imaging, Three-Dimensional
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C-arm CT imaging with the extended line-ellipse-line trajectory: first implementation on a state-of-the-art robotic angiography system.

Physics in medicine and biology Sep 18, 2020
Three-dimensional cone-beam imaging has become valuable in interventional radiology. Currently, this tool, referred to as C-arm CT, employs a circular short-scan for data acquisition, which limits the axial volume coverage and yields unavoidable cone...
Algorithms Image Processing, Computer-Assisted Artifacts Head Robotics Phantoms, Imaging Computed Tomography Angiography
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Machine Intelligence in Neurologic and Head and Neck Imaging.

Neuroimaging clinics of North America Sep 17, 2020
Diagnostic Imaging Head Head and Neck Neoplasms Humans Neck Artificial Intelligence
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