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 ...
GitHub

fhir-schema codegen

Library that generates language-specific models from FHIR StructureDefinition using type-schema (Github), enabling developers to work with strongly-typed FHIR resources in their preferred programming ...
GitHub

Zero encoding extreme performance binary serializer for C# and Unity.

Compared with System.Text.Json, protobuf-net, MessagePack for C#, Orleans.Serialization. Measured by .NET 7 / Ryzen 9 5950X machine. These serializers have IBufferWriter<byte> method, serialized using ...
NerdWallet

Is First Class Worth It?

Use points and miles to shave a little bit off the cost of first class on international flights. This page includes information about these cards, currently unavailable on NerdWallet. The information ...
IEEE

Reinforcing Adversarial Transferability via Negative Class Guided Example Generation

Abstract: Recent studies have revealed that Deep Neural Networks (DNNs) are highly vulnerable to adversarial examples, which are generated by introducing imperceptible perturbations to clean images, ...