Oil Spill Identification using Deep Convolutional Neural Networks-Reference-Cited by-同舟云学术

登录注册会员服务联系我们

Oil Spill Identification using Deep Convolutional Neural Networks

Published:2022-12-04 Issue: Volume: Page:
ISSN:
Container-title:2022 14th International Conference on Computational Intelligence and Communication Networks (CICN)
language:
Short-container-title:

Author:

Feinauer David M.¹,Latif Ghazanfar²,Alenazy Abeer M.²,Tayem Nizar³,Alghazo Jaafar¹,Alzubaidi Loay⁴

Affiliation:

1. Virginia Military Institute,Department of Electrical and Computer Engineering,Lexington,VA,USA

2. Prince Mohammad Bin Fahd University,Computer Science Department,Khobar,Saudi Arabia

3. Texas A&M University,Department of Engineering and Technology,Commerce,USA

4. Higher Colleges of Technology,Faculty of Computer Information Systems,United Arab Emirates

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10008224/10008233/10008373.pdf?arnumber=10008373

Reference28 articles.

1. Oil Spill Monitoring of Shipborne Radar Image Features Using SVM and Local Adaptive Threshold

2. Pol-SAR Based Oil Spillage Classification With Various Scenarios of Prior Knowledge

3. Protecting oceans from illicit oil spills: environment control and remote sensing using spaceborne imaging radars

4. Oil Spill Detection and Mapping Using Sentinel 2 Imagery

5. Oil spill segmentation in SAR images using convolutional neural networks. A comparative analysis with clustering and logistic regression algorithms

Cited by 4 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. Marine oil spill detection and segmentation in SAR data with two steps Deep Learning framework;Marine Pollution Bulletin;2024-07

2. Detection of AI-written and Human-written Text using Deep Recurrent Neural Networks;PROC SPIE;2024

3. Exploring Automatic Malware Detection Through Deep Learning Models;2023 Congress in Computer Science, Computer Engineering, & Applied Computing (CSCE);2023-07-24

4. Oil spills detection from SAR Earth observations based on a hybrid CNN transformer networks;Marine Pollution Bulletin;2023-05

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号京ICP备18003416号-3