AIMC Topic: Deep Learning

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Optimal Deep Learning-Based Vocal Fold Disorder Detection and Classification Model on High-Speed Video Endoscopy.

Journal of healthcare engineering
The use of high-speed video-endoscopy (HSV) in the study of phonatory processes linked to speech needs the precise identification of vocal fold boundaries at the time of vibration. The HSV is a unique laryngeal imaging technology that captures intrac...

Species level mapping of a seagrass bed using an unmanned aerial vehicle and deep learning technique.

PeerJ
BACKGROUND: Seagrass beds are essential habitats in coastal ecosystems, providing valuable ecosystem services, but are threatened by various climate change and human activities. Seagrass monitoring by remote sensing have been conducted over past deca...

Multiple Sclerosis Diagnosis Using Machine Learning and Deep Learning: Challenges and Opportunities.

Sensors (Basel, Switzerland)
Multiple Sclerosis (MS) is a disease that impacts the central nervous system (CNS), which can lead to brain, spinal cord, and optic nerve problems. A total of 2.8 million are estimated to suffer from MS. Globally, a new case of MS is reported every f...

A Hard Voting Policy-Driven Deep Learning Architectural Ensemble Strategy for Industrial Products Defect Recognition and Classification.

Sensors (Basel, Switzerland)
Manual or traditional industrial product inspection and defect-recognition models have some limitations, including process complexity, time-consuming, error-prone, and expensiveness. These issues negatively impact the quality control processes. There...

PD-BertEDL: An Ensemble Deep Learning Method Using BERT and Multivariate Representation to Predict Peptide Detectability.

International journal of molecular sciences
Peptide detectability is defined as the probability of identifying a peptide from a mixture of standard samples, which is a key step in protein identification and analysis. Exploring effective methods for predicting peptide detectability is helpful f...

Development and validation of a deep learning-based laparoscopic system for improving video quality.

International journal of computer assisted radiology and surgery
PURPOSE: A clear surgical field of view is a prerequisite for successful laparoscopic surgery. Surgical smoke, image blur, and lens fogging can affect the clarity of laparoscopic imaging. We aimed to develop a real-time assistance system (namely LVQI...

Improving Lateral Resolution in 3-D Imaging With Micro-beamforming Through Adaptive Beamforming by Deep Learning.

Ultrasound in medicine & biology
There is an increased desire for miniature ultrasound probes with small apertures to provide volumetric images at high frame rates for in-body applications. Satisfying these increased requirements makes simultaneous achievement of a good lateral reso...

Deep-Learning-Based Character Recognition from Handwriting Motion Data Captured Using IMU and Force Sensors.

Sensors (Basel, Switzerland)
Digitizing handwriting is mostly performed using either image-based methods, such as optical character recognition, or utilizing two or more devices, such as a special stylus and a smart pad. The high-cost nature of this approach necessitates a cheap...

Emotional-Health-Oriented Urban Design: A Novel Collaborative Deep Learning Framework for Real-Time Landscape Assessment by Integrating Facial Expression Recognition and Pixel-Level Semantic Segmentation.

International journal of environmental research and public health
Emotional responses are significant for understanding public perceptions of urban green space (UGS) and can be used to inform proposals for optimal urban design strategies to enhance public emotional health in the times of COVID-19. However, most emp...

Deep learning-based behavioral profiling of rodent stroke recovery.

BMC biology
BACKGROUND: Stroke research heavily relies on rodent behavior when assessing underlying disease mechanisms and treatment efficacy. Although functional motor recovery is considered the primary targeted outcome, tests in rodents are still poorly reprod...