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Found 8 papers, 5 papers with code
Finite-Time Analysis of On-Policy Heterogeneous Federated Reinforcement Learning
In response, we introduce FedSARSA, a novel federated on-policy reinforcement learning scheme, equipped with linear function approximation, to address these challenges and provide a comprehensive finite-time error analysis.
Revealing Vulnerabilities in Stable Diffusion via Targeted Attacks
In this study, we formulate the problem of targeted adversarial attack on Stable Diffusion and propose a framework to generate adversarial prompts.
Attention-Enhanced Co-Interactive Fusion Network (AECIF-Net) for Automated Structural Condition Assessment in Visual Inspection
Efficiently monitoring the condition of civil infrastructure requires automating the structural condition assessment in visual inspection.
Skeleton Graph-based Ultrasound-CT Non-rigid Registration
Autonomous ultrasound (US) scanning has attracted increased attention, and it has been seen as a potential solution to overcome the limitations of conventional US examinations, such as inter-operator variations.
A Multitask Deep Learning Model for Parsing Bridge Elements and Segmenting Defect in Bridge Inspection Images
Quantitative and qualitative results from evaluating the developed multitask deep model demonstrate its advantages over the single-task-based model not only in performance (2. 59% higher mIoU on bridge parsing and 1. 65% on corrosion segmentation) but also in computational time and implementation capability.
A Deep Neural Network for Multiclass Bridge Element Parsing in Inspection Image Analysis
Aerial robots such as drones have been leveraged to perform bridge inspections.
Visual Commonsense in Pretrained Unimodal and Multimodal Models
Our commonsense knowledge about objects includes their typical visual attributes; we know that bananas are typically yellow or green, and not purple.
Ranked #1 on
Visual Commonsense Tests
on ViComTe-color
SwapMix: Diagnosing and Regularizing the Over-Reliance on Visual Context in Visual Question Answering
By swapping the context object features, the model reliance on context can be suppressed effectively.
