Efficient land desertification detection using a deep learning‐driven generative adversarial network approach: A case study-Reference-Cited by-同舟云学术

Efficient land desertification detection using a deep learning‐driven generative adversarial network approach: A case study

Published:2021-09-12 Issue:4 Volume:34 Page:
ISSN:1532-0626
Container-title:Concurrency and Computation: Practice and Experience
language:en
Short-container-title:Concurrency and Computation

Author:

Zerrouki Nabil¹,Dairi Abdelkader²³^ORCID,Harrou Fouzi⁴^ORCID,Zerrouki Yacine⁵,Sun Ying⁴^ORCID

Affiliation:

1. Design and Implementation of Intelligent Machines (DIIM) Team Center for Development of Advanced Technologies Baba Hassen Algeria

2. LCPTS, Faculty of Electronics and Computer Science University of Sciences and Technology Houari Boumédienne Algiers Algeria

3. Department of Computer Science University of Science and Technology of Oran‐Mohamed Boudiaf (USTO‐MB) Bir El Djir Algeria

4. Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division King Abdullah University of Science and Technology (KAUST) Thuwal Saudi Arabia

5. Conservatoire National des Formations à l'Environnement Bab El Oued Algeria

Funder

King Abdullah University of Science and Technology

Publisher

Wiley

Subject

Computational Theory and Mathematics,Computer Networks and Communications,Computer Science Applications,Theoretical Computer Science,Software

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/cpe.6604

Reference36 articles.

1. Spatiotemporal Variations in Grassland Desertification Based on Landsat Images and Spectral Mixture Analysis in Yanchi County of Ningxia, China

2. Present and future of desertification in Spain: Implementation of a surveillance system to prevent land degradation

3. Monitoring land sensitivity to desertification in Central Asia: Convergence or divergence?

4. HarrouF ZerroukiN SunY HociniL.Monitoring land‐cover changes by combining a detection step with a classification step. Proceedings of the IEEE Symposium Series on Computational Intelligence (SSCI); 2018:1651‐1655.

5. Complex Adaptive Systems, soil degradation and land sensitivity to desertification: A multivariate assessment of Italian agro-forest landscape

Cited by 6 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Identification and factor analysis of rocky desertification severity levels in large-scale karst areas based on deep learning image segmentation;Ecological Indicators;2024-10

2. Deforestation detection using deep learning-based semantic segmentation techniques: a systematic review;Frontiers in Forests and Global Change;2024-02-02

3. Desertification Control Strategies: A Hybrid Approach Using Cellular Automata and Reinforcement Learning;Lecture Notes in Computer Science;2024

4. A Survey of Deep Learning for Remote Sensing, Earth Intelligence and Decision Making;Lecture Notes in Electrical Engineering;2024

5. Machine learning algorithm for estimating karst rocky desertification in a peak-cluster depression basin in southwest Guangxi, China;Scientific Reports;2022-11-09