Deep learning model predicts which heart-failure patients will worsen within a year

Characterized by weakened or damaged heart musculature, heart failure results in the gradual buildup of fluid in a patient's lungs, legs, feet, and other parts of the body. The condition is chronic ...
Frontiers

The Potential Applications of Artificial Intelligence in Immunodeficiencies

You will be redirected to our submission process. Inborn errors of immunity (IEI), formerly known as primary immunodeficiencies, represent a heterogeneous group of more than 480 genetic disorders ...
AZoOptics

AI-Enhanced Optical Spectroscopy for On-Line Food Quality Monitoring

AI-enhanced optical spectroscopy revolutionizes food quality monitoring with rapid, non-destructive analysis, ensuring safety and reducing waste in production.
IEEE

A Multiscale Deep Learning Framework with Genetic Algorithm-Optimised Inception Architecture for Defect Classification of Polyacrylonitrile Nanofibers

Abstract: Automating defect classification in electrospun polyacrylonitrile (PAN) nanofibers is essential for improving quality control and reducing the experimental effort required for scanning ...
IEEE

Automatic Detection and Classification of Printed Circuit Board Ink Printing Defects Based on Deep Learning Technique

As the core component of modern electronic products, printed circuit boards (PCBs) are widely used in various fields, from consumer electronics to aerospace. The quality of PCBs is directly related to ...
Scientific Research Publishing

Cheng, J.C.P. and Wang, M. (2018) Automated Detection of Sewer Pipe Defects in Closed-Circuit Television Images Using Deep Learning Techniques. Automation in Construction, 95 ...

ABSTRACT: Regular pipeline inspections are crucial for timely identification of critical defects and ensuring pipeline integrity. To address the challenges of detecting defects in PE gas pipelines ...
Scientific Research Publishing

BCN-YOLO: A Deep Learning Network for PCB Defect Detection ()

To address the issues of missed detection and false detection during the defect inspection process of the PCB, an improved YOLOv7-based algorithm for PCB defect detection is proposed. Firstly, the ...