AIMC Topic: Humans

Clear Filters Showing 43141 to 43150 of 95995 articles

Sentiment Analysis of Image with Text Caption using Deep Learning Techniques.

Computational intelligence and neuroscience
People are actively expressing their views and opinions via the use of visual pictures and text captions on social media platforms, rather than just publishing them in plain text as a consequence of technical improvements in this field. With the adve...

Influence of Different Passing Methods of Physical Fitness in Football Using Deep Learning.

Computational intelligence and neuroscience
Deep learning is a new direction in the field of machine learning, which learns the inherent laws and levels of data sample representation. The information gained during learning plays an important role in interpreting data such as text, images, and ...

Evolutionary Game Analysis of Farmers' Conservation Tillage Behavior in Black Soil Areas Guided by Deep Learning.

Computational intelligence and neuroscience
To better protect the rights and interests of farmers, the evolutionary game theory and deep learning (DL) technology are used to analyze the conservation tillage behavior of farmers in black soil areas. Firstly, the basic hypotheses are put forward ...

Evaluation of Traditional Culture Teaching Efficiency by Course Ideological and Political Integration Lightweight Deep Learning.

Computational intelligence and neuroscience
With the development of society, China pays more and more attention to cultural education. The teaching method of introducing ideological and political content into cultural teaching plays an important role in improving the overall teaching quality. ...

Lower-extremity fatigue fracture detection and grading based on deep learning models of radiographs.

European radiology
OBJECTIVES: To identify the feasibility of deep learning-based diagnostic models for detecting and assessing lower-extremity fatigue fracture severity on plain radiographs.

Can deep learning improve image quality of low-dose CT: a prospective study in interstitial lung disease.

European radiology
OBJECTIVES: To investigate whether deep learning reconstruction (DLR) could keep image quality and reduce radiation dose in interstitial lung disease (ILD) patients compared with HRCT reconstructed with hybrid iterative reconstruction (hybrid-IR).

Automated quantification of meibomian gland dropout in infrared meibography using deep learning.

The ocular surface
PURPOSE: Develop a deep learning-based automated method to segment meibomian glands (MG) and eyelids, quantitatively analyze the MG area and MG ratio, estimate the meiboscore, and remove specular reflections from infrared images.

Deep learning based low-activity PET reconstruction of [C]PiB and [F]FE-PE2I in neurodegenerative disorders.

NeuroImage
PURPOSE: Positron Emission Tomography (PET) can support a diagnosis of neurodegenerative disorder by identifying disease-specific pathologies. Our aim was to investigate the feasibility of using activity reduction in clinical [F]FE-PE2I and [C]PiB PE...

Sharing Rewards Undermines Coordinated Hunting.

Journal of computational biology : a journal of computational molecular cell biology
Coordinated hunting is widely observed in animals, and sharing rewards is often considered a major incentive for its success. While current theories about the role played by sharing in coordinated hunting are based on correlational evidence, we revea...

Speckle-Based Optical Cryptosystem and its Application for Human Face Recognition via Deep Learning.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Face recognition has become ubiquitous for authentication or security purposes. Meanwhile, there are increasing concerns about the privacy of face images, which are sensitive biometric data and should be protected. Software-based cryptosystems are wi...