Bias-Compensation Augmentation Learning for Semantic Segmentation in UAV Networks

T Yu, H Yang, J Nie, Q Yao, W Liu… - IEEE Internet of …, 2024 - ieeexplore.ieee.org
In the realm of emergency disaster relief, it is paramount to attain a thorough comprehension
of the semantic information associated with the local disaster scene for strategic rescue path …

Attention based semantic segmentation on uav dataset for natural disaster damage assessment

T Chowdhury, M Rahnemoonfar - 2021 IEEE International …, 2021 - ieeexplore.ieee.org
The detrimental impacts of climate change include stronger and more destructive hurricanes
happening all over the world. Identifying different damaged structures of an area including …

Adaptive path planning for UAVs for multi-resolution semantic segmentation

F Stache, J Westheider, F Magistri, C Stachniss… - Robotics and …, 2023 - Elsevier
Efficient data collection methods play a major role in helping us better understand the Earth
and its ecosystems. In many applications, the usage of unmanned aerial vehicles (UAVs) for …

[HTML][HTML] KDP-Net: An Efficient Semantic Segmentation Network for Emergency Landing of Unmanned Aerial Vehicles

Z Zhang, Y Zhang, S Xiang, L Wei - Drones, 2024 - mdpi.com
As the application of UAVs becomes more and more widespread, accidents such as
accidental injuries to personnel, property damage, and loss and destruction of UAVs due to …

[HTML][HTML] RescueNet: a high resolution UAV semantic segmentation dataset for natural disaster damage assessment

M Rahnemoonfar, T Chowdhury, R Murphy - Scientific data, 2023 - nature.com
Recent advancements in computer vision and deep learning techniques have facilitated
notable progress in scene understanding, thereby assisting rescue teams in achieving …

[PDF][PDF] Attention for damage assessment

T Chowdhury, M Rahnemoonfar - … 2021 Workshop on …, 2021 - s3.us-east-1.amazonaws.com
Due to climate change the hurricanes are getting stronger and having longer impacts. To
reduce the detrimental effects of these hurricanes faster and accurate assessments of …

Rescuenet: A high resolution post disaster uav dataset for semantic segmentation

M Rahnemoonfar, T Chowdhury, R Murphy - UMBC Student Collection, 2021 - mdsoar.org
Due to climate change, we can observe a recent surge of natural disasters all around the
world. These disasters are causing disastrous impact on both nature and human lives …

[HTML][HTML] Deep Learning-Based Semantic Segmentation of Urban Areas Using Heterogeneous Unmanned Aerial Vehicle Datasets

A Song - Aerospace, 2023 - mdpi.com
Deep learning techniques have recently shown remarkable efficacy in the semantic
segmentation of natural and remote sensing (RS) images. However, these techniques …

RescueNet: A high resolution UAV semantic segmentation benchmark dataset for natural disaster damage assessment

M Rahnemoonfar, T Chowdhury, R Murphy - arXiv preprint arXiv …, 2022 - arxiv.org
Recent advancements in computer vision and deep learning techniques have facilitated
notable progress in scene understanding, thereby assisting rescue teams in achieving …

Methods and datasets on semantic segmentation for Unmanned Aerial Vehicle remote sensing images: A review

J Cheng, C Deng, Y Su, Z An, Q Wang - ISPRS Journal of Photogrammetry …, 2024 - Elsevier
Abstract Unmanned Aerial Vehicle (UAV) has seen a dramatic rise in popularity for remote-
sensing image acquisition and analysis in recent years. It has brought promising results in …