arXiv:2606. 14081v1 Announce Type: cross Abstract: Rapid post-event landslide mapping is essential for disaster response but remains difficult to automate due to extreme class imbalance.
By Huong Binh Vu
arXiv:2606. 14081v2 Announce Type: replace-cross Abstract: Rapid post-event landslide mapping is essential for disaster response but remains difficult to automate due to extreme class imbalance.
By Huong Binh Vu
arXiv:2208. 00657v2 Announce Type: cross Abstract: Building detection and change detection using remote sensing images can help urban and rescue planning.
By Amir Mohammadian, Foad Ghaderi
arXiv:2606. 14886v1 Announce Type: cross Abstract: In the present article, an improved Knowledge Distillation (KD) framework has been proposed for efficient compression of deep convolutional neural networks for land-use image classification task.
By Arundhuti Sur, Abhiroop Chatterjee, Susmita Ghosh, Emmett Ientilucci
Timely, high-resolution maps of flood extent around settlements are essential for emergency response and damage assessment. We consider airborne RGB imagery for flood mapping as it can be collected rapidly at low cost.
Filtering noise is a fundamental part of data preparation that enhances image quality for applications such as object segmentation, detection, and recognition. Various noise reduction techniques are proposed in the literature, including the use of median, Gaussian, and bilateral filters.