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Mild cognitive impairment prediction based on multi-stream convolutional neural networks.

BMC bioinformatics
BACKGROUND: Mild cognitive impairment (MCI) is the transition stage between the cognitive decline expected in normal aging and more severe cognitive decline such as dementia. The early diagnosis of MCI plays an important role in human healthcare. Cur...

Research on fatigue detection of flight trainees based on face EMF feature model combination with PSO-CNN algorithm.

Scientific reports
Even though the capability of aircraft manufacturing has improved, human factors still play a pivotal role in flight accidents. For example, fatigue-related accidents are a common factor in human-led accidents. Hence, pilots' precise fatigue detectio...

Grading facial aging: Comparing the clinical assessments made by three dermatologists with those obtained by an AI-based scoring system that analyses selfie pictures. A focus on Chinese subjects of both genders.

International journal of cosmetic science
OBJECTIVE: The objective of this study is to assess the correspondence, in live conditions, between clinical gradings of facial aging signs by three dermatologists and those afforded by an automatic AI-based algorithm that analyses smartphones' selfi...

Enhancing facial feature de-identification in multiframe brain images: A generative adversarial network approach.

Progress in brain research
The collection of head images for public datasets in the field of brain science has grown remarkably in recent years, underscoring the need for robust de-identification methods to adhere with privacy regulations. This paper elucidates a novel deep le...

TriCAFFNet: A Tri-Cross-Attention Transformer with a Multi-Feature Fusion Network for Facial Expression Recognition.

Sensors (Basel, Switzerland)
In recent years, significant progress has been made in facial expression recognition methods. However, tasks related to facial expression recognition in real environments still require further research. This paper proposes a tri-cross-attention trans...

Leveraging 3D convolutional neural network and 3D visible-near-infrared multimodal imaging for enhanced contactless oximetry.

Journal of biomedical optics
SIGNIFICANCE: Monitoring oxygen saturation ( ) is important in healthcare, especially for diagnosing and managing pulmonary diseases. Non-contact approaches broaden the potential applications of measurement by better hygiene, comfort, and capabilit...

Empowering High-Level Spinal Cord Injury Patients in Daily Tasks With a Hybrid Gaze and FEMG-Controlled Assistive Robotic System.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Individuals with high-level spinal cord injuries often face significant challenges in performing essential daily tasks due to their motor impairments. Consequently, the development of reliable, hands-free human-computer interfaces (HCI) for assistive...

Face Omron Ring: Proactive defense against face forgery with identity awareness.

Neural networks : the official journal of the International Neural Network Society
In the era of Artificial Intelligence Generated Content (AIGC), face forgery models pose significant security threats. These models have caused widespread negative impacts through the creation of forged products targeting public figures, national lea...

Optimization of the automated Sunnybrook Facial Grading System - Improving the reliability of a deep learning network with facial landmarks.

European annals of otorhinolaryngology, head and neck diseases
OBJECTIVE: The Sunnybrook Facial Grading System (SFGS) is a well-established grading system to assess the severity and progression of a unilateral facial palsy. The automation of the SFGS makes the SFGS more accessible for researchers, students, clin...

ST-Phys: Unsupervised Spatio-Temporal Contrastive Remote Physiological Measurement.

IEEE journal of biomedical and health informatics
Remote photoplethysmography (rPPG) is a non-contact method that employs facial videos for measuring physiological parameters. Existing rPPG methods have achieved remarkable performance. However, the success mainly profits from supervised learning ove...