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Found 8 papers, 5 papers with code
Self Supervised Vision for Climate Downscaling
The improved downscaling performance and no dependence on high-resolution ground truth data make the proposed method a valuable tool for climate research and mark it as a promising direction for future research.
Generating High-Resolution Regional Precipitation Using Conditional Diffusion Model
Previous research has demonstrated the effectiveness of deep learning for downscaling tasks.
An AI-Guided Data Centric Strategy to Detect and Mitigate Biases in Healthcare Datasets
The adoption of diagnosis and prognostic algorithms in healthcare has led to concerns about the perpetuation of bias against disadvantaged groups of individuals.
GraphFC: Customs Fraud Detection with Label Scarcity
Custom officials across the world encounter huge volumes of transactions.
The Internet of Federated Things (IoFT): A Vision for the Future and In-depth Survey of Data-driven Approaches for Federated Learning
The Internet of Things (IoT) is on the verge of a major paradigm shift.
Active Learning for Human-in-the-Loop Customs Inspection
We study the human-in-the-loop customs inspection scenario, where an AI-assisted algorithm supports customs officers by recommending a set of imported goods to be inspected.
DATE: Dual Attentive Tree-aware Embedding for Customs Fraud Detection
Intentional manipulation of invoices that lead to undervaluation of trade goods is the most common type of customs fraud to avoid ad valorem duties and taxes.
Risk Communication in Asian Countries: COVID-19 Discourse on Twitter
This finding calls for a need to analyze the public discourse by new measures, such as topical dynamics.
Social and Information Networks
