Results 21 to 30 of about 2,091 (213)
Remote Sensing, 2021 Ship detection is an important but challenging task in the field of computer vision, partially due to the minuscule ship objects in optical remote sensing images and the interference of clouds occlusion and strong waves.
Liqiong Chen, Wenxuan Shi, Dexiang Deng
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A Novel Salient Feature Fusion Method for Ship Detection in Synthetic Aperture Radar Images
IEEE Access, 2020 Ship detection of synthetic aperture radar (SAR) images is one of the research hotspots in the field of marine surveillance. Fusing salient features to detection network can effectively improve the precision of ship detection. However, how to effectively
Gang Zhang +4 more
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Data-driven fraud detection in international shipping [PDF]
Expert Systems with Applications, 2018 Document fraud constitutes a growing problem in international shipping. Shipping documentation may be deliberately manipulated to avoid shipping restrictions or customs duties. Well-known examples of such fraud are miscoding and smuggling. These are cases in which the documentation of a shipment does not correctly or entirely describe the goods in ...
Triepels, Ron +2 more
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Review of plant disease image recognition algorithms based on deep learning
Dianzi Jishu YingyongPlant diseases pose a significant threat to agricultural production and food security, making timely and accurate identification and treatment critical. This article reviews the current status, challenges, and future directions of deep learning in plant ...
Yang Hankun +3 more
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IEEE Journal of Selected Topics in Applied Earth Observations and Remote SensingShip detection and identification is the key part of the maritime monitoring and safety. Ship monitoring methods based on coastal video surveillance, satellite imagery, and synthetic aperture radar have been well developed. As the emerging remote sensing
Wenjin Huang +7 more
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Ship Detection: Parameter Server Variant
CoRR, 2020 Deep learning ship detection in satellite optical imagery suffers from false positive occurrences with clouds, landmasses, and man-made objects that interfere with correct classification of ships, typically limiting class accuracy scores to 88\%. This work explores the tensions between customization strategies, class accuracy rates, training times, and
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, 2010 Der Beitrag beschreibt die Entwicklung des GMES "Near Real Time" Ship-Detection Service am DLR Standort Neustrelitz, sowie die Einbindung in das Projekt European Maritime Security Service MARISS.
Schwarz, Egbert +2 more
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SDFSD-v1.0: A Sub-Meter SAR Dataset for Fine-Grained Ship Detection
Remote SensingIn the field of target detection, a prominent area is represented by ship detection in SAR imagery based on deep learning, particularly for fine-grained ship detection, with dataset quality as a crucial factor influencing detection accuracy.
Peixin Cai +7 more
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IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021 Ship detection by an airborne passive interferometric microwave sensor has been proposed as a powerful complementary tool for ship detection, especially for large ships in low visibility conditions and high sea clutter.
Hailiang Lu +11 more
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Journal of Ocean Engineering and ScienceA Two-Dimensional Convolutional Neural Network (2D-CNN)-based multi-feature fusion detection method is proposed to improve the detection performance of the submarine wake magnetic anomaly in view of its characteristics of low frequency and low signal-to ...
Ran Hui +3 more
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