Search Results for author:
Found 8 papers, 5 papers with code
Using an Uncrewed Surface Vehicle to Create a Volumetric Model of Non-Navigable Rivers and Other Shallow Bodies of Water
Non-navigable rivers and retention ponds play important roles in buffering communities from flooding, yet emergency planners often have no data as to the volume of water that they can carry before flooding the surrounding.
Improving Drone Imagery For Computer Vision/Machine Learning in Wilderness Search and Rescue
This paper describes gaps in acquisition of drone imagery that impair the use with computer vision/machine learning (CV/ML) models and makes five recommendations to maximize image suitability for CV/ML post-processing.
Open Problems in Computer Vision for Wilderness SAR and The Search for Patricia Wu-Murad
This paper details the challenges in applying two computer vision systems, an EfficientDET supervised learning model and the unsupervised RX spectral classifier, to 98. 9 GB of drone imagery from the Wu-Murad wilderness search and rescue (WSAR) effort in Japan and identifies 3 directions for future research.
RescueNet: A High Resolution UAV Semantic Segmentation Benchmark Dataset for Natural Disaster Damage Assessment
Recent advancements in computer vision and deep learning techniques have facilitated notable progress in scene understanding, thereby assisting rescue teams in achieving precise damage assessment.
FloodNet: A High Resolution Aerial Imagery Dataset for Post Flood Scene Understanding
This dataset demonstrates the post flooded damages of the affected areas.
Comprehensive Semantic Segmentation on High Resolution UAV Imagery for Natural Disaster Damage Assessment
In this paper, we present a large-scale hurricane Michael dataset for visual perception in disaster scenarios, and analyze state-of-the-art deep neural network models for semantic segmentation.
Explicit-risk-aware Path Planning with Reward Maximization
Without manual assignment of the negative impact to the planner caused by risk, this planner takes in a pre-established viewpoint quality map and plans target location and path leading to it simultaneously, in order to maximize overall reward along the entire path while minimizing risk.
Visual Servoing of Unmanned Surface Vehicle from Small Tethered Unmanned Aerial Vehicle
The motor schema proposed, uses the USVs coordinates from the visual localization subsystem to control the UAVs camera movements and track the USV with minimal camera movements such that the USV is always in the cameras field of view.
