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Navigating Indoors With Computer Vision: Using Deep Learning for Room-Level Indoor Localisation
In my bachelor thesis I investigated whether state-of-the-art deep learning architectures for image and video classification (CNNs, CRNNs, Transformers) can accuractely predict where a human is located in an indoor environment given only information from the camera feed.
Thesis
Computer Vision
Deep Learning
Work & Publications
2023
Advancing Homepage2Vec with LLM-Generated Datasets for Multilingual Website Classification
Unlocking the Palate - A Data-Centric Approach to Understanding Beer Descriptors
Benchmarking SOT Feature Transform for Biomedical Few-Shot Learning Tasks
Navigating Indoors with Computer Vision - Deep Learning Approaches for Room-Level Indoor Localisation
M. SenghaasS. Grasshof
2022
2021
Weighted Bipartite Graph Projection Methods for a GitHub Recommender System
Projects & Initiatives
Selected Lecture Notes
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© Mika Senghaas 2024