A new study published in Science Advances presents a method that converts human brain activity into coherent, descriptive ...
Abstract: Malware poses a growing cybersecurity threat, rendering traditional signature-based detection methods insufficient against evolving attack strategies. Many existing machine learning (ML) ...
Abstract: Classification of human activities performed sequentially and with unconstrained durations using radar sensors has been studied in this work. A novel processing pipeline comprising a ...
A six-metabolite plasma panel was developed and validated for gastric cancer (GC) diagnosis using UPLC-MS and machine ...
Machine learning, a key enabler of artificial intelligence, is increasingly used for applications like self-driving cars, medical devices, and advanced robots that work near humans — all contexts ...
Background: Eczema and psoriasis are common chronic dermatoses with overlapping features, making early differential diagnosis difficult. While biopsy is the gold standard, its invasiveness and ...
Cybersecurity professionals recognize that enterprise networks are prime targets for dark web risks such as ransomware, unauthorized insider activity, and data exfiltration. What’s less obvious is ...
Stem cell-derived embryo models are crucial for advancing our knowledge of early human development.University of Cambridge Researchers at the University of Cambridge have found a new way to produce ...
IC manufacturers are increasingly relying on intelligent data processing to prevent downtime, improve yields, and reduce scrap. They are integrating that with fault detection and classification (FDC) ...
Image Forgery Detection is a web-based application designed to detect and analyze potential image manipulations and forgeries. Developed in Python using the Django framework, it provides an easy and ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results
Feedback