Nature

Automatic Modulation Classification Using Deep Learning Techniques

Automatic modulation classification (AMC) is an essential technology in modern communications, enabling the identification of various signal modulation schemes without prior knowledge, thereby ...
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 ...
EurekAlert!

To know what you do not know: An evidential deep learning framework for traffic classification

Traffic classification is a crucial task for network security. One of the most difficult challenges is to accurately identify the traffic of unknown applications as well as discriminate the known ...
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 ...
The American Journal of Managed Care

Machine Learning–Based Classifier Accurately Identifies Ovarian Cancer

A predictive model utilizing serum metabolic profiles was able to distinguish ovarian cancer from control samples with 93% accuracy, according to a new study. Machine learning–based classification ...
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 ...
ascopubs.org

Non-invasive colorectal cancer detection using multimodal deep learning ensemble classifier.

Effect of breast tissue density on cell-free orphan non-coding RNAs secreted by breast cancers. Nature and distribution of methyl thioadenosine phosphorylase (MTAP) genomic loss in human tumors. This ...
ascopubs.org

Image-Based Subtype Classification for Glioblastoma Using Deep Learning: Prognostic Significance and Biologic Relevance

Using whole-slide hematoxylin and eosin images from 214 patients with glioblastoma in The Cancer Genome Atlas (TCGA), a fine-tuned convolutional neural network model extracted deep learning features.
Scientific Research Publishing

UWB NLOS Signal Recognition Based on Deep Learning ()

However, in indoor environments, non-line-of-sight (NLOS) signals significantly degrade the ranging performance of UWB ...
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 ...
Analytics Insight

Best PyTorch Courses to Learn Deep Learning in 2026

PyTorch is one of the most popular tools for building AI and deep learning models in 2026.The best PyTorch courses teach both basic concept ...
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 ...