5 papers
RareSpot+: A Benchmark, Model, and Active Learning Framework for Small and Rare Wildlife in Aerial Imagery
Bowen Zhang, Jesse T. Boulerice, Charvi Mendiratta +4
Automated wildlife monitoring from aerial imagery is vital for conservation but remains limited by two persistent challenges: the difficulty of detecting small, rare species and th…
Markovian Reeb Graphs for Simulating Spatiotemporal Patterns of Life
Anantajit Subrahmanya, Chandrakanth Gudavalli, Connor Levenson +1
Accurately modeling human mobility is critical for urban planning, epidemiology, and traffic management. In this work, we introduce Markovian Reeb Graphs, a novel framework that tr…
Hyperspectral Trajectory Image for Multi-Month Trajectory Anomaly Detection
Md Awsafur Rahman, Chandrakanth Gudavalli, Hardik Prajapati +1
Trajectory anomaly detection underpins applications from fraud detection to urban mobility analysis. Dense GPS methods preserve fine-grained evidence such as abnormal speeds and sh…
GPS-MTM: Capturing Pattern of Normalcy in GPS-Trajectories with self-supervised learning
Umang Garg, Bowen Zhang, Anantajit Subrahmanya +2
Foundation models have driven remarkable progress in text, vision, and video understanding, and are now poised to unlock similar breakthroughs in trajectory modeling. We introduce…
RareSpot: Spotting Small and Rare Wildlife in Aerial Imagery with Multi-Scale Consistency and Context-Aware Augmentation
Bowen Zhang, Jesse T. Boulerice, Nikhil Kuniyil +4
Automated detection of small and rare wildlife in aerial imagery is crucial for effective conservation, yet remains a significant technical challenge. Prairie dogs exemplify this i…