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70 results found

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

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

A Synthetic Methodology for Preparing Impregnated and Grafted Amine-Based Silica-Composites for Carbon Capture

Data provided by  National Institute of Standards and Technology

The database includes thermal data analysis for silica-composites that conclude the loading amount of amine adsorbents of each composite as well as each specimen's ability to adsorb CO2. The data repository includes raw data files for: thermogravimetric analysis (TGA) weight loss and CO2 adsorption traces, and Fourier Transform Infrared Spectroscopy (FTIR) spectra?s. For more information see the readme and data documentation. A complete manuscript describing data collection, analysis, and database documentation is to be published. File formats for data include: .txt and .csv.

Tags: FTIR,thermal analysis,DSC,TGA,optical microscopy,Advanced Materials,direct air capture materials,

Modified: 2024-02-22

Views: 0

Trojan Detection Software Challenge - nlp-summary-jan2022-test

Data provided by  National Institute of Standards and Technology

Round 9 Test DatasetThis is the test data used to evaluate trojan detection software solutions. This data, generated at NIST, consists of natural language processing (NLP) AIs trained to perform one of three tasks, sentiment classification, named entity recognition, or extractive question answering on English text. 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.

Tags: Trojan Detection; Artificial Intelligence; AI; Machine Learning; Adversarial Machine Learning;,

Modified: 2024-02-22

Views: 0

Trojan Detection Software Challenge - nlp-summary-jan2022-holdout

Data provided by  National Institute of Standards and Technology

Round 9 Holdout DatasetThis is the holdout data used to evaluate trojan detection software solutions. This data, generated at NIST, consists of natural language processing (NLP) AIs trained to perform one of three tasks, sentiment classification, named entity recognition, or extractive question answering on English text. 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.

Tags: Trojan Detection; Artificial Intelligence; AI; Machine Learning; Adversarial Machine Learning;,

Modified: 2024-02-22

Views: 0

Trojan Detection Software Challenge - object-detection-jul2022-train

Data provided by  National Institute of Standards and Technology

Round 10 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 on the COCO 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 144 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

Thermal Conductivity of Binary Mixtures of 1,1,1,2-Tetrafluoroethane(R-134a), 2,3,3,3-Tetrafluoropropene (R-1234yf), and trans-1,3,3,3-Tetrafluoropropene (R-1234ze(E)) Refrigerants

Data provided by  National Institute of Standards and Technology

Workflow: The data that falls into this category are gathered from a measurement program and are published in the archival literature.

Tags: Advanced Materials,Energy,Environment and Climate,Physical Infrastructure,Safety,Security and Forensics,

Modified: 2024-02-22

Views: 0

Speed of Sound Measurements of Binary Mixtures of Difluoromethane (R-32) with 2,3,3,3-Tetrafluoropropene (R-1234yf) or trans-1,3,3,3-Tetrafluoropropene (R-1234ze(E)) Refrigerants

Data provided by  National Institute of Standards and Technology

Speed of Sound Measurements of Binary Mixtures of Difluoromethane (R-32) with 2,3,3,3-Tetrafluoropropene (R-1234yf) or trans-1,3,3,3-Tetrafluoropropene (R-1234ze(E)) Refrigerants

Tags: Advanced Materials,Energy,Environment and Climate,Physical Infrastructure,Safety,Security and Forensics,

Modified: 2024-02-22

Views: 0

4D-STEM characterization results from a thermal annealing series of poly(3[2-(2-methoxyethoxy)ethoxy]-methylthiophene-2,5-diyl) organic electrochemical transistor films

Data provided by  National Institute of Standards and Technology

This repository contains two types of datasets: 4D-STEM data collected from a thermal annealing series of P3MEEMT films. 4D-STEM data:Dose series: Collected from P3MEEMT film annealed at 115 C. Each HDF5 file was generated from the raw data using the fpdpy software package to reshape and embed metadata. No other preprocessing was performed. Annealing series: Collected from P3MEEMT films annealed at 75 C, 115 C, 145 C, and 175 C. Each temperature contains two sets of 4D-STEM data collected at low and high magnification.

Tags: Advanced Materials,Organic Semiconductors,4D-STEM,OECT,TEM,GIWAXS,

Modified: 2024-02-22

Views: 0