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Found 6 papers, 6 papers with code
Magnifier: A Multi-grained Neural Network-based Architecture for Burned Area Delineation
In particular, the local and global encoders extract information from the same input at different granularities.
Level Up Your Tutorials: VLMs for Game Tutorials Quality Assessment
Our approach leverages VLMs to analyze frames from video game tutorials, answer relevant questions to simulate human perception, and provide feedback.
ViGEO: an Assessment of Vision GNNs in Earth Observation
Satellite missions and Earth Observation (EO) systems represent fundamental assets for environmental monitoring and the timely identification of catastrophic events, long-term monitoring of both natural resources and human-made assets, such as vegetation, water bodies, forests as well as buildings.
CaBuAr: California Burned Areas dataset for delineation
Forest wildfires represent one of the catastrophic events that, over the last decades, caused huge environmental and humanitarian damages.
ITALIC: An Italian Intent Classification Dataset
Recent large-scale Spoken Language Understanding datasets focus predominantly on English and do not account for language-specific phenomena such as particular phonemes or words in different lects.
Attention to Fires: Multi-Channel Deep Learning Models for Wildfire Severity Prediction
In this context, we analyze the burned area severity estimation problem by exploiting a state-of-the-art deep learning framework.
