IEEE

Data ID Extraction Networks for Unsupervised Class- and Classifier-Free Detection of Adversarial Examples

Abstract: Deep neural networks (DNNs) have achieved satisfactory performance in multiple fields. However, recent studies have shown that DNNs can be easily fooled by adversarial examples. To mitigate ...
The Decatur Daily

How to Learn Data Science with Python in 2026: The Complete Beginner-to-Job-Ready Roadmap

A large amount of time and resources have been invested in making Python the most suitable first programming language for ...
InfoQ

Java 26 Delivers Language Innovation, Library Improvements, Performance and Security

Oracle has released version 26 of the Java programming language and virtual machine. As the first non-LTS release since JDK ...
InfoQ

QCon London 2026: Ontology‐Driven Observability: Building the E2E Knowledge Graph at Netflix Scale

Silva, both Engineers at Netflix, presented “Ontology‐Driven Observability: Building the E2E Knowledge Graph at Netflix Scale ...
IEEE

A Study of Data Augmentation for Learning-Driven Scientific Visualization

Abstract: The success of deep learning heavily relies on the large amount of training samples. However, in scientific visualization, due to the high computational cost, only few data are available ...