5 citations · 21 across the 18 of their papers we have counts for
18 papers
GeoSAM-3D: Geodesic Prompt Propagation for Open-Vocabulary 3D Scene Segmentation from Monocular Video
Arun Sharma
Open-vocabulary 3D scene segmentation usually assumes RGB-D video, calibrated multi-view imagery, or a reconstructed mesh. GeoSAM-3D studies a lighter setting: a user uploads a sho…
DarkVesselNet: Multi-Modal Remote Sensing and Trajectory Reasoning for Dark Vessel Detection
Arun Sharma
Dark vessel detection requires fusing what vessels report through AIS with what satellites observe through radar and optical sensors. DarkVesselNet is a multi-modal remote sensing…
Towards Fine-Tuning-Based Site Calibration for Knowledge-Guided Machine Learning: A Summary of Results
Ruolei Zeng, Arun Sharma, Shuai An +5
Accurate and cost-effective quantification of the agroecosystem carbon cycle at decision-relevant scales is essential for climate mitigation and sustainable agriculture. However, b…
Towards Physics-informed Diffusion for Anomaly Detection in Trajectories
Arun Sharma, Mingzhou Yang, Majid Farhadloo +3
Given trajectory data, a domain-specific study area, and a user-defined threshold, we aim to find anomalous trajectories indicative of possible GPS spoofing (e.g., fake trajectory)…
Towards Physics-Guided Foundation Models
Majid Farhadloo, Arun Sharma, Mingzhou Yang +3
Traditional foundation models are pre-trained on broad datasets to reduce the training resources (e.g., time, energy, labeled samples) needed for fine-tuning a wide range of downst…
Spatial Distribution-Shift Aware Knowledge-Guided Machine Learning
Arun Sharma, Majid Farhadloo, Mingzhou Yang +3
Given inputs of diverse soil characteristics and climate data gathered from various regions, we aimed to build a model to predict accurate land emissions. The problem is important…
Spatially-Delineated Domain-Adapted AI Classification: An Application for Oncology Data
Majid Farhadloo, Arun Sharma, Alexey Leontovich +2
Given multi-type point maps from different place-types (e.g., tumor regions), our objective is to develop a classifier trained on the source place-type to accurately distinguish be…
Towards Kriging-informed Conditional Diffusion for Regional Sea-Level Data Downscaling
Subhankar Ghosh, Arun Sharma, Jayant Gupta +2
Given coarser-resolution projections from global climate models or satellite data, the downscaling problem aims to estimate finer-resolution regional climate data, capturing fine-s…
Towards Statistically Significant Taxonomy Aware Co-location Pattern Detection
Subhankar Ghosh, Arun Sharma, Jayant Gupta +1
Given a collection of Boolean spatial feature types, their instances, a neighborhood relation (e.g., proximity), and a hierarchical taxonomy of the feature types, the goal is to fi…
Reducing False Discoveries in Statistically-Significant Regional-Colocation Mining: A Summary of Results
Subhankar Ghosh, Jayant Gupta, Arun Sharma +2
Given a set \emph{S} of spatial feature types, its feature instances, a study area, and a neighbor relationship, the goal is to find pairs a region (), a subset \emph{C}…
Physics-Guided Abnormal Trajectory Gap Detection
Arun Sharma, Shashi Shekhar
Given trajectories with gaps (i.e., missing data), we investigate algorithms to identify abnormal gaps in trajectories which occur when a given moving object did not report its loc…
Towards Spatially-Lucid AI Classification in Non-Euclidean Space: An Application for MxIF Oncology Data
Majid Farhadloo, Arun Sharma, Jayant Gupta +3
Given multi-category point sets from different place-types, our goal is to develop a spatially-lucid classifier that can distinguish between two classes based on the arrangements o…
Reducing Uncertainty in Sea-level Rise Prediction: A Spatial-variability-aware Approach
Subhankar Ghosh, Shuai An, Arun Sharma +3
Given multi-model ensemble climate projections, the goal is to accurately and reliably predict future sea-level rise while lowering the uncertainty. This problem is important becau…
Spatial Computing Opportunities in Biomedical Decision Support: The Atlas-EHR Vision
Majid Farhadloo, Arun Sharma, Shashi Shekhar +1
We consider the problem of reducing the time needed by healthcare professionals to understand patient medical history via the next generation of biomedical decision support. This p…
Towards a Tighter Bound on Possible-Rendezvous Areas: Preliminary Results
Arun Sharma, Jayant Gupta, Subhankar Ghosh
Given trajectories with gaps, we investigate methods to tighten spatial bounds on areas (e.g., nodes in a spatial network) where possible rendezvous activity could have occurred. T…
Spatiotemporal Data Mining: A Survey
Arun Sharma, Zhe Jiang, Shashi Shekhar
Spatiotemporal data mining aims to discover interesting, useful but non-trivial patterns in big spatial and spatiotemporal data. They are used in various application domains such a…
Understanding COVID-19 Effects on Mobility: A Community-Engaged Approach
Arun Sharma, Majid Farhadloo, Yan Li +3
Given aggregated mobile device data, the goal is to understand the impact of COVID-19 policy interventions on mobility. This problem is vital due to important societal use cases, s…
An End-to-End System for Crowdsourced 3d Maps for Autonomous Vehicles: The Mapping Component
Onkar Dabeer, Radhika Gowaikar, Slawomir K. Grzechnik +5
Autonomous vehicles rely on precise high definition (HD) 3d maps for navigation. This paper presents the mapping component of an end-to-end system for crowdsourcing precise 3d maps…