Nature

Automatic Mineral Classification Using Deep Learning Techniques

Recent advances in deep learning have significantly transformed mineral classification methodologies, supplanting labour‐intensive manual approaches with automated, high-precision systems. By ...
Scientific Research Publishing

A Lightweight MobileViT with a Dual-Path Attention Mechanism for MRI Image Classification ()

Deep learning has been successfully applied in the field of medical diagnosis, and improving the accurate classification of ...
Scientific Research Publishing

Hybrid Deep Learning Model for Breast Cancer Classification in Low-Middle Income Countries: A MobileNetV2 and Cubic SVM ()

Breast cancer is one of the major causes of female death in any part of the world, and the burden is highly ...
pv magazine International

PV fault detection method based on deep learning of aerial images

An international research team has developed a novel PV fault detection method based on deep learning of aerial images. The proposed methodology utilizes the convolutional neural network (CNN) ...
AZoRobotics

AI Model Achieves 99.24 % Accuracy in Breast Ultrasound Classification

This study presents a deep learning model for breast cancer detection, achieving 99.24% accuracy and improving clinical ...
Semiconductor Engineering

Using Deep Learning ADC For Defect Classification For Automatic Defect Inspection

In traditional semiconductor packaging, manual defect review after automated optical inspection (AOI) is an arduous task for operators and engineers, involving review of both good and bad die. It is ...
Business Wire

GE HealthCare Expands Its Effortless Recon DL Portfolio, Bringing Advanced Deep Learning Image Reconstruction to Clinicians Worldwide

CHICAGO--(BUSINESS WIRE)--GE HealthCare (Nasdaq: GEHC) unveiled three new advanced deep learning image processing and reconstruction solutions as a part of its Effortless Recon DL portfolio at the ...
Analytics Insight

Best Neural Networks Courses in 2026 for AI and Deep Learning

Overview Neural networks courses in 2026 focus heavily on practical deep learning frameworks such as TensorFlow, PyTorch, and Keras.Growing demand for AI profes ...