Displaying 14 resources
Video/Webinars Video/Webinars

Webinar "Towards Transparent, Safe and Trustworthy AI for critical infrastructures"

This webinar focuses on the development of safe, explainable, and algorithmically transparent methods as part of the AI4REALNET project.

Category
Action and Interaction Technologies, Data for AI, Reasoning and decision-making Technologies, Sensing and perception technologies, Systems, methodologies, hardware, and tools
Target audience
ADR Experts and Associations, Policy Makers, Private Sector, Public Sector, Researchers and Academic
Source
Adra-e
Video/Webinars Video/Webinars

Webinar: Knowledge-Assisted AI Applications for Real-World Network Infrastructure

This webinar showcases how the AI4REALNET project is driving innovation in critical infrastructure through advanced AI applications.

Category
Action and Interaction Technologies, Data for AI, Reasoning and decision-making Technologies, Sensing and perception technologies, Systems, methodologies, hardware, and tools
Target audience
ADR Experts and Associations, Policy Makers, Private Sector, Public Sector, Researchers and Academic
Source
Adra-e
Article/Books/eBooks Article/Books/eBooks

An Open Dataset of Synthetic Speech

This paper introduces a multilingual, multispeaker dataset composed of synthetic and natural speech, designed to foster research and benchmarking in synthetic speech detection.

Category
Semantic knowledge, Technology methodologies and landscape
Target audience
ADR Experts and Associations, Researchers and Academic
Source
Adra-e
Software resources Software resources

Word-Class Embeddings for Multiclass Text Classification

Code for Word-Class Embeddings (WCEs), a form of supervised embeddings especially suited for multiclass text classification.

Category
Semantic knowledge, Technology methodologies and landscape
Target audience
ADR Experts and Associations, Researchers and Academic
Source
Adra-e
Software resources Software resources

Neighborhood Contrastive Learning for Novel Class Discovery

A holistic learning framework for Novel Class Discovery (NCD), which adopts contrastive learning to learn discriminate features with both the labeled and unlabeled data.

Category
Semantic knowledge
Target audience
ADR Experts and Associations, Researchers and Academic
Source
Adra-e
Software resources Software resources

Style-Hallucinated Dual Consistency Learning for Domain Generalized Semantic Segmentation

we study the task of synthetic-to-real domain generalized semantic segmentation, which aims to learn a model that is robust to unseen real-world scenes using only synthetic data.

Category
Semantic knowledge
Target audience
ADR Experts and Associations, Researchers and Academic
Source
Adra-e