Simultaneous extraction of roads and buildings in remote sensing imagery with convolutional neural networks

By Rasha Alshehhi, Prashanth Reddy Marpu, Wei Lee Woon, M. Dalla Mura. 2017

383 citations recorded by the source corpus.

Subfields: Environmental Engineering, Media Technology, Ocean Engineering

View Paper: https://www.semanticscholar.org/paper/ca8e0614c16e09966d8e97caf485bdbc511f38ab

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Environmental Engineering

1. Lichuan Gu
2. Xiaohui Yuan
3. Jianfang Shi

In Media Technology

1. Zhenfeng Shao
2. Weixun Zhou
3. Congmin Li
4. Shawn D. Newsam
5. Lichuan Gu
6. Xiaohui Yuan
7. Jianfang Shi
8. Liangpei Zhang

Citations in the corpus

• PatternNet: A Benchmark Dataset for Performance Evaluation of Remote Sensing Image Retrieval (2017, background): “, 2015) as well as remote sensing problems such as simultaneous roads and buildings extraction (Alshehhi et al., 2017), veryhigh-resolution optical image (Zhao et al.”
• A review of deep learning methods for semantic segmentation of remote sensing imagery (2021, methodology): “Alshehhi, Marpu, Woon, and Dalla Mura (2017) used color similarity and spatial proximity based on pixel coordinates and applied SLIC to generate an initial image segmentation result.”