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72 results found

Trojan Detection Software Challenge - image-classification-aug2020-holdout

Data provided by  National Institute of Standards and Technology

Round 2 Holdout DatasetThe data being generated and disseminated is the holdout data used to evaluate trojan detection software solutions. This data, generated at NIST, consists of human level AIs trained to perform a variety of tasks (image classification, natural language processing, etc.). 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 - image-classification-dec2020-test

Data provided by  National Institute of Standards and Technology

Round 3 Test DatasetThe data being generated and disseminated is the training data used to construct trojan detection software solutions. This data, generated at NIST, consists of human level AIs trained to perform image classification. 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 - image-classification-dec2020-holdout

Data provided by  National Institute of Standards and Technology

Round 3 Holdout DatasetThe data being generated and disseminated is the training data used to construct trojan detection software solutions. This data, generated at NIST, consists of human level AIs trained to perform image classification. 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 - image-classification-feb2021-train

Data provided by  National Institute of Standards and Technology

Round 4 Train DatasetThe data being generated and disseminated is the training data used to construct trojan detection software solutions. This data, generated at NIST, consists of human level AIs trained to perform image classification. 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 - image-classification-feb2021-test

Data provided by  National Institute of Standards and Technology

Round 4 Test DatasetThe data being generated and disseminated is the test data used to construct trojan detection software solutions. This data, generated at NIST, consists of human level AIs trained to perform image classification. 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 - image-classification-feb2021-holdout

Data provided by  National Institute of Standards and Technology

Round 4 Holdout DatasetThe data being generated and disseminated is the holdout data used to construct trojan detection software solutions. This data, generated at NIST, consists of human level AIs trained to perform image classification. 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-sentiment-classification-mar2021-train

Data provided by  National Institute of Standards and Technology

Round 5 Train DatasetThe data being generated and disseminated is the train data used to construct trojan detection software solutions. This data, generated at NIST, consists of natural language processing (NLP) AIs trained to perform text sentiment classification 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

FIZ/NIST Inorganic Crystal Structure Database (ICSD) - SRD 84

Data provided by  National Institute of Standards and Technology

The Inorganic Crystal Structure Database (ICSD) is produced cooperatively by the Fachinformationszentrum Karlsruhe (FIZ) and the National Institute of Standards and Technology (NIST). Components and devices used in a broad spectrum of technology sectors such as health care, communications, energy and electronics are manufactured from crystalline materials; the development of advanced crystalline materials requires accurate crystal-structure data.

Tags: Rietveld profiles,X ray crystallography,X ray diffraction,X rays,XRD,absolute configurations,chemical structures,crystal data,crystal structures,crystallography,crystals,defect structures,diffraction,disorders,electron diffractions,electrons,identification,inorganic,inorganic structures,magnetic structures,materials,metals,mineral names,minerals,mixed crystal solid solutions,mixed crystals,modulated structures,neutron diffractions,neutrons,nuclear magnetic resonance,polytype structures,powder simulations,power,powers,prediction,simulations,single crystals,structure predictions,structures,synchroton radiations,twinned crystals,visualizations,x ray diffractions,

Modified: 2024-02-22

Views: 0

NIST/ARPA-E Database of Novel and Emerging Adsorbent Materials

Data provided by  National Institute of Standards and Technology

The NIST/ARPA-E Database of Novel and Emerging Adsorbent Materials is a free, web-based catalog of adsorbent materials and measured adsorption properties of numerous materials obtained from article entries from the scientific literature. Search fields for the database include adsorbent material, adsorbate gas, experimental conditions (pressure, temperature), and bibliographic information (author, title, journal), and results from queries are provided as a list of articles matching the search parameters.

Tags: adsorbate,adsorbent,adsorption,isotherm,metal organic Framework,porous Material,surface science,Advanced Materials,Energy,Environment and Climate,manufacturing,

Modified: 2024-02-22

Views: 0

SRM 1877 Beryllium Oxide Powder

Data provided by  National Institute of Standards and Technology

SRM 1877 Beryllium Oxide Powder - This Standard Reference Material (SRM) is intended for use in laboratory analysis and health research for the development and validation of analytical methods and instruments used to determine beryllium, as well as for proficiency testing of laboratories involved in beryllium determinations. A unit of SRM 1877 consists of one bottle containing 20 g of beryllium oxide powder. This data is public in the Certificate of Analysis for this material.

Tags: Advanced Materials,

Modified: 2024-02-22

Views: 0