SAR ship detection dataset (SSDD): Official release and comprehensive data analysis
SAR Ship Detection Dataset (SSDD) is the first open dataset that is widely used to research
state-of-the-art technology of ship detection from Synthetic Aperture Radar (SAR) imagery …
state-of-the-art technology of ship detection from Synthetic Aperture Radar (SAR) imagery …
Deep learning for SAR ship detection: Past, present and future
J Li, C Xu, H Su, L Gao, T Wang - Remote Sensing, 2022 - mdpi.com
After the revival of deep learning in computer vision in 2012, SAR ship detection comes into
the deep learning era too. The deep learning-based computer vision algorithms can work in …
the deep learning era too. The deep learning-based computer vision algorithms can work in …
Rethinking rotated object detection with gaussian wasserstein distance loss
Boundary discontinuity and its inconsistency to the final detection metric have been the
bottleneck for rotating detection regression loss design. In this paper, we propose a novel …
bottleneck for rotating detection regression loss design. In this paper, we propose a novel …
Dense label encoding for boundary discontinuity free rotation detection
Rotation detection serves as a fundamental building block in many visual applications
involving aerial image, scene text, and face etc. Differing from the dominant regression …
involving aerial image, scene text, and face etc. Differing from the dominant regression …
Lite-yolov5: A lightweight deep learning detector for on-board ship detection in large-scene sentinel-1 sar images
Synthetic aperture radar (SAR) satellites can provide microwave remote sensing images
without weather and light constraints, so they are widely applied in the maritime monitoring …
without weather and light constraints, so they are widely applied in the maritime monitoring …
Dense attention pyramid networks for multi-scale ship detection in SAR images
Z Cui, Q Li, Z Cao, N Liu - IEEE Transactions on Geoscience …, 2019 - ieeexplore.ieee.org
Synthetic aperture radar (SAR) is an active microwave imaging sensor with the capability of
working in all-weather, all-day to provide high-resolution SAR images. Recently, SAR …
working in all-weather, all-day to provide high-resolution SAR images. Recently, SAR …
An anchor-free method based on feature balancing and refinement network for multiscale ship detection in SAR images
Recently, deep-learning methods have been successfully applied to the ship detection in the
synthetic aperture radar (SAR) images. It is still a great challenge to detect multiscale SAR …
synthetic aperture radar (SAR) images. It is still a great challenge to detect multiscale SAR …
LS-SSDD-v1. 0: A deep learning dataset dedicated to small ship detection from large-scale Sentinel-1 SAR images
Ship detection in synthetic aperture radar (SAR) images is becoming a research hotspot. In
recent years, as the rise of artificial intelligence, deep learning has almost dominated SAR …
recent years, as the rise of artificial intelligence, deep learning has almost dominated SAR …
Deep learning meets SAR: Concepts, models, pitfalls, and perspectives
Deep learning in remote sensing has received considerable international hype, but it is
mostly limited to the evaluation of optical data. Although deep learning has been introduced …
mostly limited to the evaluation of optical data. Although deep learning has been introduced …
Squeeze and excitation rank faster R-CNN for ship detection in SAR images
Z Lin, K Ji, X Leng, G Kuang - IEEE Geoscience and Remote …, 2018 - ieeexplore.ieee.org
Synthetic aperture radar (SAR) ship detection is an important part of marine monitoring. With
the development in computer vision, deep learning has been used for ship detection in SAR …
the development in computer vision, deep learning has been used for ship detection in SAR …