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Found 7 papers, 1 papers with code
Reinforcement Learning from Diffusion Feedback: Q* for Image Search
We present two models for image generation using model-agnostic learning that align semantic priors with generative capabilities.
t-RAIN: Robust generalization under weather-aliasing label shift attacks
We present state-of-the-art pedestrian detection results on real and synthetic weather domains with best performing 82. 69 AP (snow) and 62. 31 AP (fog) respectively.
WEDGE: A multi-weather autonomous driving dataset built from generative vision-language models
WEDGE consists of 3360 images in 16 extreme weather conditions manually annotated with 16513 bounding boxes, supporting research in the tasks of weather classification and 2D object detection.
In Rain or Shine: Understanding and Overcoming Dataset Bias for Improving Robustness Against Weather Corruptions for Autonomous Vehicles
Methods to mitigate such bias which allows the OD models to perform better and improve the robustness are also demonstrated.
RestoreX-AI: A Contrastive Approach towards Guiding Image Restoration via Explainable AI Systems
Modern applications such as self-driving cars and drones rely heavily upon robust object detection techniques.
Investigating the Relationship Between World Development Indicators and the Occurrence of Disease Outbreaks in the 21st Century: A Case Study
In this paper, we leverage data driven models to determine the relationship between the trends of World Development Indicators and occurrence of disease outbreaks using worldwide historical data from 2000-2019, and treat it as a classic supervised classification problem.
Modelling Major Disease Outbreaks in the 21st Century: A Causal Approach
Epidemiologists aiming to model the dynamics of global events face a significant challenge in identifying the factors linked with anomalies such as disease outbreaks.
