- vision
- language
- time series
- multimodal
- embedded
- internship
- thesis
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Unsupervised Alignment of Geo-Embeddings for Rapid Disaster Mapping
Learning to align pre-computed geospatial embeddings with post-event satellite features for unsupervised disaster delineation without bi-temporal inference.
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Graph Neural Networks for Urban Heat Island Forecasting using Satellite data
Development of a GNN-based architecture operating on satellite imagery, urban topology, and meteorological data to predict neighborhood-scale temperature distributions.
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Efficient Adaptation of Vision–Language Models for Artistic Metadata Generation
This thesis involves specializing Vision–Language Models (VLMs) for multimodal artistic metadata generation through parameter-efficient fine-tuning and knowledge distillation approaches.
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Deep Learning for wildfire spread modeling
The thesis aims at developing a Deep Learning model to predict wildfire spread using multimodal and multivariate data.
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Beyond the Canvas: A Systematic Review of Generative AI for Image Synthesis and Editing
Providing a comprehensive review of state-of-the-art image generative models, exploring architectural evolutions from GANs to Diffusion Models and hybrid systems, while analyzing evaluation paradigms and ethical challenges.