130 citations · 133 across the 4 of their papers we have counts for
4 papers
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…
Attention Based Semantic Segmentation on UAV Dataset for Natural Disaster Damage Assessment
Tashnim Chowdhury, Maryam Rahnemoonfar
The detrimental impacts of climate change include stronger and more destructive hurricanes happening all over the world. Identifying different damaged structures of an area includi…
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…