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 ...
Nature

Cataract Detection and Classification Using Deep Learning Techniques

Cataracts remain a leading cause of visual impairment worldwide, necessitating prompt and accurate diagnosis to avert irreversible blindness. In recent years, deep learning has emerged as a ...
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 ...
Seeking Alpha

MicroAlgo Inc. Develops Classifier Auto-Optimization Technology Based on Variational Quantum Algorithms, Accelerating the Advancement of Quantum Machine Learning

SHENZHEN, China, May 2, 2025 /PRNewswire/ -- MicroAlgo Inc. (MLGO) (the "Company" or "MicroAlgo") announced today the launch of their latest classifier auto-optimization technology based on ...
EurekAlert!

New ensemble AI model enhances cyber intrusion detection with high accuracy

A study published in The Journal of Engineering Research (TJER) at Sultan Qaboos University presents an advanced intrusion detection system (IDS) designed to improve the accuracy and efficiency of ...
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.
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 ...
Devdiscourse

IoT and ensemble AI transform congestion prediction in urban bus networks

However, inconsistent travel times and unpredictable congestion continue to undermine service reliability, particularly in ...
Technology Networks

Machine Learning Applications in Proteomics

Machine learning enhances proteomics by optimizing peptide identification, structure prediction, and biomarker discovery.