A Survey on Edge Detection based recent Marine Horizon Line Detection Methods and their Applications

Hashmani, Manzoor Ahmed; Umair, Muhammad; Rizvi, Syed Sajjad Hussain; Gilal, Abdul Rehman

doi:10.1109/icomet48670.2020.9073895

Cited by 7 publications

(3 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…2019 [74] comprehensive overview of edge detection based on recent marine horizon line detection, and challenging problem in SANET 2020 [75] A survey on marine vehicles with the guidance and control methodologies in SANET 2021 [76] Review in most used technologies for underwater networking, a trade-off between underwater properties, wireless communication technologies, and communication quality in SANET.…”

Section: Reference Major Contribution Yearmentioning

confidence: 99%

Moving Ad Hoc Networks—A Comparative Study

Al-Absi

Sain

et al. 2021

Sustainability

View full text Add to dashboard Cite

An ad hoc network is a wireless mobile communication network composed of a group of mobile nodes with wireless transceivers. It does not rely on preset infrastructure and is established temporarily. The mobile nodes of the network use their own wireless transceivers to exchange information; when the information is not within the communication range, other intermediate nodes can be used to relay to achieve communication. They can be widely used in environments that cannot be supported by wired networks or which require communication temporarily, such as military applications, sensor networks, rescue and disaster relief, and emergency response. In MANET, each node acts as a host and as a router, and the nodes are linked through wireless channels in the network. One of the scenarios of MANET is VANET; VANET is supported by several types of fixed infrastructure. Due to its limitations, this infrastructure can support some VANET services and provide fixed network access. FANET is a subset of VANET. SANET is one of the common types of ad hoc networks. This paper could serve as a guide and reference so that readers have a comprehensive and general understanding of wireless ad hoc networks and their routing protocols at a macro level with a lot of good, related papers for reference. However, this is the first paper that discusses the popular types of ad hoc networks along with comparisons and simulation tools for Ad Hoc Networks.

show abstract

Section: Reference Major Contribution Yearmentioning

confidence: 99%

Moving Ad Hoc Networks—A Comparative Study

Al-Absi

Sain

et al. 2021

Sustainability

View full text Add to dashboard Cite

show abstract

“…Marine horizon detection is the most significant semantic boundary for segmenting the image into sea and sky. References [18,19] have summarized the marine horizon line detection. In the past research, many robust marine horizon generation methods have been proposed.…”

Section: Horizon Detectionmentioning

confidence: 99%

“…Moniruzzaman et al [17] described the use of deep learning for underwater imagery analysis, and deep learning architectures have been highlighted. Hashmani et al [18] presented a survey on edge detection-based and machine learning-based marine horizon line detection; each study is presented with a recommendation for their suitability for a specific application in the marine environment.…”

Section: Introductionmentioning

confidence: 99%

Survey on Deep Learning-Based Marine Object Detection

Zhang

et al. 2021

Journal of Advanced Transportation

View full text Add to dashboard Cite

We present a survey on marine object detection based on deep neural network approaches, which are state-of-the-art approaches for the development of autonomous ship navigation, maritime surveillance, shipping management, and other intelligent transportation system applications in the future. The fundamental task of maritime transportation surveillance and autonomous ship navigation is to construct a reachable visual perception system that requires high efficiency and high accuracy of marine object detection. Therefore, high-performance deep learning-based algorithms and high-quality marine-related datasets need to be summarized. This survey focuses on summarizing the methods and application scenarios of maritime object detection, analyzes the characteristics of different marine-related datasets, highlights the marine detection application of the YOLO series model, and also discusses the current limitations of object detection based on deep learning and possible breakthrough directions. The large-scale, multiscenario industrialized neural network training is an indispensable link to solve the practical application of marine object detection. A widely accepted and standardized large-scale marine object verification dataset should be proposed.

show abstract

Multilevel thresholding of images with improved Otsu thresholding by black widow optimization algorithm

ALRAHLAWEE>

Rahebi

2021

Multimed Tools Appl

View full text Add to dashboard Cite

A Survey on Edge Detection based recent Marine Horizon Line Detection Methods and their Applications

Cited by 7 publications

References 17 publications

Moving Ad Hoc Networks—A Comparative Study

Moving Ad Hoc Networks—A Comparative Study

Survey on Deep Learning-Based Marine Object Detection

Multilevel thresholding of images with improved Otsu thresholding by black widow optimization algorithm

Contact Info

Product

Resources

About