Results 21 to 30 of about 3,027,178 (230)

Polarimetric SAR ship detection based on superpixel and sparse reconstruction saliency

open access: yes工程科学学报, 2023
Polarimetric SAR ship detection is an important application of the polarimetric SAR system. Existing polarimetric SAR ship detection methods are plagued by erroneous detection of strong clutter and missed detection of small targets in multiscale ...
Jiahao LUO, Junjun YIN, Jian YANG
doaj   +1 more source

Quad-FPN: A Novel Quad Feature Pyramid Network for SAR Ship Detection

open access: yesRemote Sensing, 2021
Ship detection from synthetic aperture radar (SAR) imagery is a fundamental and significant marine mission. It plays an important role in marine traffic control, marine fishery management, and marine rescue.
Tianwen Zhang, Xiaoling Zhang, Xiao Ke
doaj   +1 more source

Gaussian Function Fusing Fully Convolutional Network and Region Proposal-Based Network for Ship Target Detection in SAR Images

open access: yesInternational Journal of Antennas and Propagation, 2022
Recently, ship target detection in Synthetic aperture radar (SAR) images has become one of the current research hotspots and plays an important role in the real-time detection of sea regions.
Peipei Zhang, Guokun Xie, Jinsong Zhang
doaj   +1 more source

Improved Ship Detection Algorithm Based on YOLOX for SAR Outline Enhancement Image

open access: yesRemote Sensing, 2022
Synthetic aperture radar (SAR) ship detection based on deep learning has the advantages of high accuracy and end-to-end processing, which has received more and more attention.
Sen Li, Xiongjun Fu, Jian Dong
doaj   +1 more source

Multi-Sensor-Based Hierarchical Detection and Tracking Method for Inland Waterway Ship Chimneys

open access: yesJournal of Marine Science and Engineering, 2022
In the field of automatic detection of ship exhaust behavior, a deep learning-based multi-sensor hierarchical detection method for tracking inland river ship chimneys is proposed to locate the ship exhaust behavior detection area quickly and accurately ...
Fumin Wu   +4 more
doaj   +1 more source

Feature Enhancement Pyramid and Shallow Feature Reconstruction Network for SAR Ship Detection

open access: yesIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2023
Recently, convolutional neural network based methods have been studied for ship detection in optical remote sensing images. However, it is challenging to apply them to microwave synthetic aperture radar (SAR) images.
Lin Bai   +5 more
doaj   +1 more source

The Surface Warfare Test Ship [PDF]

open access: yes, 1999
Web page capture of TSSE Team 1999 - The Surface Warfare Test Ship project page, as it appeared July 2, 2025.The Surface Warfare Test Ship (SWTS) project was a systems engineering approach to the design of a ship conversion to satisfy the needs of the ...

core   +2 more sources

A Ship Rotation Detection Model in Remote Sensing Images Based on Feature Fusion Pyramid Network and Deep Reinforcement Learning

open access: yesRemote Sensing, 2018
Ship detection plays an important role in automatic remote sensing image interpretation. The scale difference, large aspect ratio of ship, complex remote sensing image background and ship dense parking scene make the detection task difficult.
Kun Fu   +6 more
doaj   +1 more source

YOLF-ShipPnet: Improved RetinaNet with Pyramid Vision Transformer

open access: yesInternational Journal of Computational Intelligence Systems, 2023
In the field of ship detection, the intricate nature of ship images arises from a multitude of factors, including variations in ship orientation, color contrasts, and diverse shapes.
Zhiruo Qiu, Shiyang Rong, Likun Ye
doaj   +1 more source

PPA-Net: Pyramid Pooling Attention Network for Multi-Scale Ship Detection in SAR Images

open access: yesRemote Sensing, 2023
In light of recent advances in deep learning and Synthetic Aperture Radar (SAR) technology, there has been a growing adoption of ship detection models that are based on deep learning methodologies.
Gang Tang   +6 more
doaj   +1 more source

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