SOTAVerified

Dataset Generation

The task involves enhancing the training of target application (e.g. autonomous driving systems) by generating datasets of diverse and critical elements (e.g. traffic scenarios). Traditional methods rely on expensive and limited datasets, which often fail to capture rare but essential situations that can pose risks during testing.

Papers

Showing 201210 of 308 papers

TitleStatusHype
RAG vs Fine-tuning: Pipelines, Tradeoffs, and a Case Study on Agriculture0
Automatic UAV-based Airport Pavement Inspection Using Mixed Real and Virtual Scenarios0
Model-Driven Dataset Generation for Data-Driven Battery SOH Models0
RainSD: Rain Style Diversification Module for Image Synthesis Enhancement using Feature-Level Style Distribution0
FlowDA: Unsupervised Domain Adaptive Framework for Optical Flow Estimation0
Fast and Knowledge-Free Deep Learning for General Game Playing (Student Abstract)0
Pipeline and Dataset Generation for Automated Fact-checking in Almost Any LanguageCode0
Large Scale Foundation Models for Intelligent Manufacturing Applications: A Survey0
A Probabilistic Neural Twin for Treatment Planning in Peripheral Pulmonary Artery Stenosis0
Learning to Compute Gröbner BasesCode0
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