Deep learning on edge: extracting field boundaries from satellite images with a convolutional neural network

26 October 2019

Papers citing "Deep learning on edge: extracting field boundaries from satellite images with a convolutional neural network"

9 / 9 papers shown

Title
Global Renewables Watch: A Temporal Dataset of Solar and Wind Energy Derived from Satellite Imagery Caleb Robinson Anthony Ortiz Allen Kim Rahul Dodhia Andrew Zolli Shivaprakash K. Nagaraju J. O J. Kiesecker J. L. Ferres 64 0 0 19 Mar 2025
Multi-Region Transfer Learning for Segmentation of Crop Field Boundaries in Satellite Images with Limited Labels Hannah Kerner Saketh Sundar Mathan Satish 30 7 0 29 Mar 2024
Productive Crop Field Detection: A New Dataset and Deep Learning Benchmark Results E. Nascimento John Just Jurandy Almeida Tiago A. Almeida 24 6 0 19 May 2023
A systematic review of the use of Deep Learning in Satellite Imagery for Agriculture Brandon Victor Zhen He Aiden Nibali 30 9 0 03 Oct 2022
Combining GEDI and Sentinel-2 for wall-to-wall mapping of tall and short crops S. D. Tommaso Sherrie Wang David B. Lobell 24 37 0 10 Sep 2021
GANmapper: geographical data translation Abraham Noah Wu Filip Biljecki GAN 21 41 0 07 Aug 2021
Panoptic Segmentation of Satellite Image Time Series with Convolutional Temporal Attention Networks Vivien Sainte Fare Garnot Loic Landrieu AI4TS 71 152 0 16 Jul 2021
Looking for change? Roll the Dice and demand Attention F. Diakogiannis F. Waldner P. Caccetta 23 66 0 04 Sep 2020
Small, Sparse, but Substantial: Techniques for Segmenting Small Agricultural Fields Using Sparse Ground Data S. Marvaniya Umamaheswari Devi J. Hazra Shashank Mujumdar Nitin Gupta 55 13 0 05 May 2020