1 citations · 1 across the 3 of their papers we have counts for
4 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…
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…
ReeFRAME: Reeb Graph based Trajectory Analysis Framework to Capture Top-Down and Bottom-Up Patterns of Life
Chandrakanth Gudavalli, Bowen Zhang, Connor Levenson +2
In this paper, we present ReeFRAME, a scalable Reeb graph-based framework designed to analyze vast volumes of GPS-enabled human trajectory data generated at 1Hz frequency. ReeFRAME…