Search Results for author:
Found 8 papers, 5 papers with code
Semantics from Space: Satellite-Guided Thermal Semantic Segmentation Annotation for Aerial Field Robots
We present a new method to automatically generate semantic segmentation annotations for thermal imagery captured from an aerial vehicle by utilizing satellite-derived data products alongside onboard global positioning and attitude estimates.
Caltech Aerial RGB-Thermal Dataset in the Wild
We present the first publicly-available RGB-thermal dataset designed for aerial robotics operating in natural environments.
Online Self-Supervised Thermal Water Segmentation for Aerial Vehicles
We present a new method to adapt an RGB-trained water segmentation network to target-domain aerial thermal imagery using online self-supervision by leveraging texture and motion cues as supervisory signals.
Efficiently-Verifiable Strong Uniquely Solvable Puzzles and Matrix Multiplication
We advance the Cohn-Umans framework for developing fast matrix multiplication algorithms.
Matrix Multiplication: Verifying Strong Uniquely Solvable Puzzles
In subsequent work with Kleinberg and Szegedy, they connected this to the search for combinatorial objects called strong uniquely solvable puzzles (strong USPs).
Machine Learning 5G Attack Detection in Programmable Logic
Machine learning-assisted network security may significantly contribute to securing 5G components.
Ranked #1 on
Low-latency processing
on 5GAD-2022
NeBula: Quest for Robotic Autonomy in Challenging Environments; TEAM CoSTAR at the DARPA Subterranean Challenge
This paper presents and discusses algorithms, hardware, and software architecture developed by the TEAM CoSTAR (Collaborative SubTerranean Autonomous Robots), competing in the DARPA Subterranean Challenge.
Independent Vector Analysis: Identification Conditions and Performance Bounds
Thus, we provide the additional conditions for when the arbitrary ordering of the sources within each dataset is common.
