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Trojan Detection Software Challenge - image-classification-sep2022-train
Data provided by National Institute of Standards and Technology
Round 11 Train DatasetThis is the training data used to create and evaluate trojan detection software solutions. This data, generated at NIST, consists of image classification AIs trained on synthetic image data build from Cityscapes. A known percentage of these trained AI models have been poisoned with a known trigger which induces incorrect behavior. This data will be used to develop software solutions for detecting which trained AI models have been poisoned via embedded triggers. This dataset consists of 288 AI models using a small set of model architectures.
Tags: Trojan Detection; Artificial Intelligence; AI; Machine Learning; Adversarial Machine Learning;,
Modified: 2024-02-22
Views: 0
A Data-Driven Approach to Complex Voxel Predictions in Grayscale Digital Light Processing Additive Manufacturing Using U-nets and Generative Adversarial Networks
Data provided by National Institute of Standards and Technology
Digital light processing (DLP) vat photopolymerization (VP) additive manufacturing (AM) uses patterned UV light to selectively cure a liquid photopolymer into a solid layer. Subsequent layers are printed on to preceding layers to eventually form a desired 3 dimensional (3D) part. This data set characterizes the 3D geometry of a single layer of voxels (volume pixels) printed with photomasks assigned random intensity levels at every pixel. The masks are computer generated, then printed onto a glass cover slide.
Tags: 3D printing,additive manufacturing,machine learning,generative adversarial network,Photopolymer,
Modified: 2024-02-22
Views: 0
Towards a Structured Evaluation Methodology for Artificial Intelligence Technology (SEMAIT) MIg analyZeR (mizr) Package
Data provided by National Institute of Standards and Technology
Our work towards a Structured Evaluation Methodology for Artificial Intelligence Technology (SEMAIT) aims to provide plots, tools, methods, and strategies to extract insights out of various machine learning (ML) and Artificial Intelligence (AI) data.Included in this software is the MIg analyZeR (mizr) R software package that produces various plots.
Tags: analysis software,Artificial Intelligence,machine learning,design of experiments,
Modified: 2024-02-22
Views: 0
Microplastic and nanoplastic chemical characterization by thermal desorption and pyrolysis mass spectrometry with unsupervised machine learning
Data provided by National Institute of Standards and Technology
This data publication contains the mass spectrometry chemical characterization of microplastic and nanoplastic chemical analysis. The data from this study includes mass spectra of pure, mixed, and weathered microplastics and nanoplastics at high and low fragmentation, extracted ion chronograms, Kendrick mass defect plots, code, and the derived and processed data. The data analysis code (MATLAB 2022a*) used for unsupervised learning of cluster and compositional relationships is also included.
Tags: Microplastic,Nanoplastics,environment,mass spectrometry,GC-MS,Chemical Characterization,machine learning,
Modified: 2024-02-22
Views: 0
Trojan Detection Software Challenge - object-detection-feb2023-train
Data provided by National Institute of Standards and Technology
Round 13 Train DatasetThis is the training data used to create and evaluate trojan detection software solutions. This data, generated at NIST, consists of object detection AIs trained both on synthetic image data build from Cityscapes and the DOTA_v2 dataset. A known percentage of these trained AI models have been poisoned with a known trigger which induces incorrect behavior. This data will be used to develop software solutions for detecting which trained AI models have been poisoned via embedded triggers. This dataset consists of 128 AI models using a small set of model architectures.
Tags: Trojan Detection; Artificial Intelligence; AI; Machine Learning; Adversarial Machine Learning;,
Modified: 2024-02-22
Views: 0
Trojan Detection Software Challenge - cyber-pdf-dec2022-train
Data provided by National Institute of Standards and Technology
Round 12 Train DatasetThis is the training data used to create and evaluate trojan detection software solutions. This data, generated at NIST, consists of pdf malware classification AIs trained Contaigio dataset feature vectors. A known percentage of these trained AI models have been poisoned with a known trigger which induces incorrect behavior. This data will be used to develop software solutions for detecting which trained AI models have been poisoned via embedded triggers. This dataset consists of 120 AI models using a small set of model architectures.
Tags: Trojan Detection; Artificial Intelligence; AI; Machine Learning; Adversarial Machine Learning;,
Modified: 2024-02-22
Views: 0
ns-3 ORAN Module
Data provided by National Institute of Standards and Technology
This module for ns-3 implements the classes required to model a network architecture based on the O-RAN Alliance's specifications. These models include a Radio Access Network (RAN) Intelligent Controller (RIC) that is functionally equivalent to O-RAN's Near-Real Time (Near-RT) RIC, and reporting modules that attach to simulation nodes and serve as communication endpoints with the RIC in a similar fashion as the E2 Terminators in O-RAN.
Tags: Artificial Intelligence,machine learning,Open RAN,RAN Intelligent Controller,
Modified: 2024-02-22
Views: 0
Noise Datasets for Evaluating Deep Generative Models
Data provided by National Institute of Standards and Technology
Synthetic training and test datasets for experiments on deep generative modeling of noise time series. Consists of data for the following noise types: 1) band-limited thermal noise, i.e., bandpass filtered white Gaussian noise, 2) power law noise, including fractional Gaussian noise (FGN), fractional Brownian motion (FBM), and fractionally differenced white noise (FDWN), 3) generalized shot noise, 4) impulsive noise, including Bernoulli-Gaussian (BG) and symmetric alpha stable (SAS) distributions.
Tags: generative adversarial network,machine learning,time series,band-limited noise,power law noise,shot noise,impulsive noise,colored noise,fractional Gaussian noise,fractional Brownian motion,
Modified: 2024-02-22
Views: 0
Data for Modeling OFDM Communication Signals with Generative Adversarial Networks
Data provided by National Institute of Standards and Technology
This repository contains results for experiments on generative modeling of synthetic Orthogonal-Frequency Division Multiplexing (OFDM) communication signals. (This record supersedes Software and Data for Modeling OFDM Communication Signals with Generative Adversarial Networks, formerly at https://doi.org/10.18434/mds2-2428)
Tags: generative adversarial network,machine learning,wireless communications,
Modified: 2024-02-22
Views: 0
Trojan Detection Software Challenge - nlp-question-answering-sep2021-test
Data provided by National Institute of Standards and Technology
Round 8 Test DatasetThis is the training data used to construct and evaluate trojan detection software solutions. This data, generated at NIST, consists of natural language processing (NLP) AIs trained to perform extractive question answering. A known percentage of these trained AI models have been poisoned with a known trigger which induces incorrect behavior. This data will be used to develop software solutions for detecting which trained AI models have been poisoned via embedded triggers. This dataset consists of 360 QA AI models using a small set of model architectures.
Tags: Trojan Detection,Artificial Intelligence,ai,machine learning,Adversarial Machine Learning,
Modified: 2024-02-22
Views: 0