7 citations · 7 across the 4 of their papers we have counts for
4 papers
DeepAndes: A Self-Supervised Vision Foundation Model for Multi-Spectral Remote Sensing Imagery of the Andes
Junlin Guo, James R. Zimmer-Dauphinee, Jordan M. Nieusma +16
By mapping sites at large scales using remotely sensed data, archaeologists can generate unique insights into long-term demographic trends, inter-regional social networks, and past…
Self-Supervised Large Scale Point Cloud Completion for Archaeological Site Restoration
Aocheng Li, James R. Zimmer-Dauphinee, Rajesh Kalyanam +4
Point cloud completion helps restore partial incomplete point clouds suffering occlusions. Current self-supervised methods fail to give high fidelity completion for large objects w…
Vision Foundation Models in Remote Sensing: A Survey
Siqi Lu, Junlin Guo, James R Zimmer-Dauphinee +5
Artificial Intelligence (AI) technologies have profoundly transformed the field of remote sensing, revolutionizing data collection, processing, and analysis. Traditionally reliant…
Semi-Supervised Contrastive Learning for Remote Sensing: Identifying Ancient Urbanization in the South Central Andes
Jiachen Xu, Junlin Guo, James Zimmer-Dauphinee +7
Archaeology has long faced fundamental issues of sampling and scalar representation. Traditionally, the local-to-regional-scale views of settlement patterns are produced through sy…