This dataset contains the images and ground truth label masks for semantic segmentation created and described in "Hinniger, C.; Rüter, J. Synthetic Training Data for Semantic Segmentation of the Environment from UAV Perspective. Aerospace 2023, 10, 604. https://doi.org/10.3390/aerospace10070604"
Video semantic segmentation has been one of the research focus in computer vision recently. It serve...
An unmanned ground vehicle (UGV) that should operate autonomously on the road as well as in the terr...
This paper describes preliminary work in the recent promising approach of generating synthetic train...
Autonomous unmanned aircraft need a good semantic understanding of their surroundings to plan safe r...
UAVid dataset is a high-resolution UAV semantic segmentation dataset focusing on street scenes. The ...
Semantic segmentation of aerial images is the ability to assign labels to all pixels of an image. It...
The classification of semantic segmentation-based unmanned aerial vehicle (UAV) application based on...
The semantic segmentation of a scene is one of the basic components towards the total understanding ...
Semantic segmentation has been one of the leading research interests in computer vision recently. It...
Semantic segmentation, also called scene labeling, refers to the process of assigning a semantic lab...
Deeplabv3+ currently is the most representative semantic segmentation model. However, Deeplabv3+ ten...
Unmanned aerial vehicles (UAV) are used to conduct a variety of recognition as well as specific miss...
Semantic segmentation for unmanned aerial vehicle (UAV) remote sensing images has become one of the ...
In this thesis, semantic mapping is understood to be the process of putting a tag or label on object...
This database contains images used for training a fully convolutional neural network for the semanti...
Video semantic segmentation has been one of the research focus in computer vision recently. It serve...
An unmanned ground vehicle (UGV) that should operate autonomously on the road as well as in the terr...
This paper describes preliminary work in the recent promising approach of generating synthetic train...
Autonomous unmanned aircraft need a good semantic understanding of their surroundings to plan safe r...
UAVid dataset is a high-resolution UAV semantic segmentation dataset focusing on street scenes. The ...
Semantic segmentation of aerial images is the ability to assign labels to all pixels of an image. It...
The classification of semantic segmentation-based unmanned aerial vehicle (UAV) application based on...
The semantic segmentation of a scene is one of the basic components towards the total understanding ...
Semantic segmentation has been one of the leading research interests in computer vision recently. It...
Semantic segmentation, also called scene labeling, refers to the process of assigning a semantic lab...
Deeplabv3+ currently is the most representative semantic segmentation model. However, Deeplabv3+ ten...
Unmanned aerial vehicles (UAV) are used to conduct a variety of recognition as well as specific miss...
Semantic segmentation for unmanned aerial vehicle (UAV) remote sensing images has become one of the ...
In this thesis, semantic mapping is understood to be the process of putting a tag or label on object...
This database contains images used for training a fully convolutional neural network for the semanti...
Video semantic segmentation has been one of the research focus in computer vision recently. It serve...
An unmanned ground vehicle (UGV) that should operate autonomously on the road as well as in the terr...
This paper describes preliminary work in the recent promising approach of generating synthetic train...
DOI
Add to ORKG