130 citations · 132 across the 4 of their papers we have counts for
4 papers
Open Problems in Computer Vision for Wilderness SAR and The Search for Patricia Wu-Murad
Thomas Manzini, Robin Murphy
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 dron…
RescueNet: A High Resolution UAV Semantic Segmentation Benchmark Dataset for Natural Disaster Damage Assessment
Maryam Rahnemoonfar, Tashnim Chowdhury, Robin Murphy
Recent advancements in computer vision and deep learning techniques have facilitated notable progress in scene understanding, thereby assisting rescue teams in achieving precise da…
FloodNet: A High Resolution Aerial Imagery Dataset for Post Flood Scene Understanding
Maryam Rahnemoonfar, Tashnim Chowdhury, Argho Sarkar +3
Visual scene understanding is the core task in making any crucial decision in any computer vision system. Although popular computer vision datasets like Cityscapes, MS-COCO, PASCAL…
Comprehensive Semantic Segmentation on High Resolution UAV Imagery for Natural Disaster Damage Assessment
Maryam Rahnemoonfar, Tashnim Chowdhury, Robin Murphy +1
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…