- vision
- language
- time series
- multimodal
- embedded
- internship
- thesis
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Improve Zero-shot Classification in Vision-Language Models by Bridging the Modality Gap
A comparison of existing methods for reducing the modality gap in pre-trained vision-language models with new approaches aimed at improving performance on downstream tasks (such as zero-shot classification).
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User Semantic Embedding in Social Media Graphs.
Develop Self-Supervised method to learn high quality semantic embedding of social media users, purely based on their activity on the graph and without relying on labelled data.
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Refactoring a Web Application for generating paintings from music
Refactoring a Web Application for generating paintings from music
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Development of a Machine-Learning-Based Recommender System for Optimizing Household Energy Consumption
Development of a Machine-Learning-Based Recommender System for Optimizing Household Energy Consumption
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Embedding AI models for GNSS signal spoofing on Maxim boards
Porting deep learning models on custom NPU-enabled boards.