most citedBuilding Privacy-Preserving and Secure Geospatial Artificial Intelligence Foundation Models

26 citations · 39 across the 6 of their papers we have counts for

collaborators

6 papers

cs.LG20237 cited

FLEE-GNN: A Federated Learning System for Edge-Enhanced Graph Neural Network in Analyzing Geospatial Resilience of Multicommodity Food Flows

Yuxiao Qu, Jinmeng Rao, Song Gao +6

Understanding and measuring the resilience of food supply networks is a global imperative to tackle increasing food insecurity. However, the complexity of these networks, with thei…

cs.AI202326 cited

Building Privacy-Preserving and Secure Geospatial Artificial Intelligence Foundation Models

Jinmeng Rao, Song Gao, Gengchen Mai +1

In recent years we have seen substantial advances in foundation models for artificial intelligence, including language, vision, and multimodal models. Recent studies have highlight…

cs.CV20233 cited

SSIF: Learning Continuous Image Representation for Spatial-Spectral Super-Resolution

Gengchen Mai, Ni Lao, Weiwei Sun +7

Existing digital sensors capture images at fixed spatial and spectral resolutions (e.g., RGB, multispectral, and hyperspectral images), and each combination requires bespoke machin…

cs.LG20232 cited

CATS: Conditional Adversarial Trajectory Synthesis for Privacy-Preserving Trajectory Data Publication Using Deep Learning Approaches

Jinmeng Rao, Song Gao, Sijia Zhu

The prevalence of ubiquitous location-aware devices and mobile Internet enables us to collect massive individual-level trajectory dataset from users. Such trajectory big data bring…

cs.CL20231 cited

Tackling Vision Language Tasks Through Learning Inner Monologues

Diji Yang, Kezhen Chen, Jinmeng Rao +4

Visual language tasks require AI models to comprehend and reason with both visual and textual content. Driven by the power of Large Language Models (LLMs), two prominent methods ha…

cs.CV2023

LOWA: Localize Objects in the Wild with Attributes

Xiaoyuan Guo, Kezhen Chen, Jinmeng Rao +3

We present LOWA, a novel method for localizing objects with attributes effectively in the wild. It aims to address the insufficiency of current open-vocabulary object detectors, wh…