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An LLM-powered TA that adapts to course material to help guide and engage students through conceptual and technical questions, focusing on reducing redundant questions and addressing overworked TAs.
Our project implements a cGAN architecture for the task of “greening” extraterrestrial imagery to earth-like satellite imagery, accomplishing this through the usage of elevation data as label maps.
