- vision
- language
- time series
- multimodal
- embedded
- internship
- thesis
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Enhancing Artwork Recognition through Attribute-Supervised Contrastive Learning
Developing a Supervised Contrastive Learning approach for artwork image datasets, leveraging artworks' metadata attributes, to enhance performances on the Artwork Instance Recognition task.
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Computer Vision-Based Damage Assessment Using Optical Remote Sensing Imagery
Developing a framework to localize and classify damage to buildings and roads in natural disaster events, by using computer vision algorithms on optical remote sensing imagery.
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Enhancing Multimodal RAG Systems through Cross-Modal Retrieval and Reranking
This thesis involves the implementation of a cross-modal retrieval and reranking pipeline.
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Machine Learning-Based Corn Yield Forecasting Using Meteorological and Agronomic Data
Develop a machine learning algorithm able to forecast the expected yield at the end of the season by analising weather data and field management data.
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Development of a PyTorch-Based Framework for Semantic Segmentation on Point Clouds
A short description of the proposal.