Search Results for author:
Found 5 papers, 1 papers with code
Neural Embedding Compression For Efficient Multi-Task Earth Observation Modelling
We introduce Neural Embedding Compression (NEC), based on the transfer of compressed embeddings to data consumers instead of raw data.
Multi-Spectral Remote Sensing Image Retrieval Using Geospatial Foundation Models
Image retrieval enables an efficient search through vast amounts of satellite imagery and returns similar images to a query.
AB2CD: AI for Building Climate Damage Classification and Detection
To achieve robust and accurate evaluations of building damage detection and classification, we evaluated different deep learning models with residual, squeeze and excitation, and dual path network backbones, as well as ensemble techniques.
Toward Foundation Models for Earth Monitoring: Generalizable Deep Learning Models for Natural Hazard Segmentation
However, DL-based approaches are designed for one specific task in a single geographic region based on specific frequency bands of satellite data.
Privacy is What We Care About: Experimental Investigation of Federated Learning on Edge Devices
Federated Learning enables training of a general model through edge devices without sending raw data to the cloud.
