Towards Generalization of Models on Streets Imagery: Methods and Applications

The domains relevant to urban planning have been disrupted by the proliferation of highly granular city data and the advancements in machine learning. However, machine learning models are susceptible to pitfalls constraining their deployment in many applications including domains related to urban...

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Bibliographic Details
Main Author: Alhasoun, Fahad
Other Authors: González, Marta C.
Format: Thesis
Published: Massachusetts Institute of Technology 2025
Online Access:https://hdl.handle.net/1721.1/158316

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