Performance analysis of rule-based classification and deep learning method for automatic road extraction

Z Bayramoğlu, M Uzar - International Journal of Engineering and …, 2023 - dergipark.org.tr
The need for accurate and up-to-date spatial data by decision-makers in public and private
administrations is increasing gradually. In recent decades, in the management of disasters …

[PDF][PDF] Building detection methods from remotely sensed images

N Chandra, H Vaidya - Current Science, 2022 - researchgate.net
With the availability of high-resolution satellite imagery, new applications have been
developed for solving geospatial issues in urban regions. Building detection from remote …

Multi deep learning model for building footprint extraction from high resolution remote sensing image

HT Anh, TA Tuan, HP Long, LH Ha… - Intelligent Systems and …, 2022 - Springer
Abstract 3D city modeling is a new development trend in cartography that has a lot of
practical and scientific value. The project necessitates the extraction of a building footprint …

Assessment of Deep Learning Based Image Segmentation for Identifying Floating Net Cages from Very High-Resolution Capella Synthetic Aperture Radar (SAR) Data

S Arjasakusuma, SS Kusuma - Journal of the Indian Society of Remote …, 2024 - Springer
The availability of a constellation remote sensing satellite system using very high resolution
(VHR) synthetic aperture radar (SAR) is beneficial to obtain information from the earth …

Aircraft segmentation algorithm based on Unet and improved Yolov4

Z Dong, H Chang, X Pu, P Luo… - … , Big Data & Smart City …, 2021 - ieeexplore.ieee.org
In order to overcome the problems of poor effect and low accuracy of semantic segmentation
of aircraft target, a small target segmentation method based on improved Yolov4 and Unet is …

An improved self-training network for building and road extraction in urban areas by integrating optical and radar remotely sensed data

R Naanjam, F Farnood Ahmadi - Earth Science Informatics, 2024 - Springer
Enhancing urban management and planning necessitates the automated and accurate
extraction of features from remotely sensed images. To address the challenges in urban …

Efficient cnn architecture for multi-modal aerial view object classification

C Miron, A Pasarica, R Timofte - Proceedings of the IEEE …, 2021 - openaccess.thecvf.com
The NTIRE 2021 workshop features a Multi-modal Aerial View Object Classification
Challenge. Its focus is on multi-sensor imagery classification in order to improve the …

Image Enhancement of 3-D SAR via U-Net Framework

R Shen, S Wei, Z Zhou, J Liang… - IGARSS 2022-2022 …, 2022 - ieeexplore.ieee.org
Image resolution is the key point for the 3-D synthetic aperture radar (SAR) application,
especially in small-scale scene observation. The traditional filter-based image enhancement …

[PDF][PDF] Exploring Models and Band Selection for Improved Contrail Detection with Deep Learning

A Rahmatulloh, VR A'izzah, I Darmawan… - Journal of Advances in …, 2024 - jait.us
The consequences of climate change are becoming increasingly urgent, with contrails
emerging as a potential contributing factor to this phenomenon. Consequently, there is an …

Performance Evaluation of DL-based Models for LULC segmentation using SAR time series data of regions in Gujarat

S Jain, N Varghese, K Joshi, P Kathiria, S Garg… - 2023 - researchsquare.com
Both spatial and non-spatial data are critical to a country's social and economic
development. Land use and land cover (LULC) maps are data that can be used to retrieve …