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   Articles with "grained ship" as a keyword



DSNet: dual-stream network for fine-grained ship classification in optical remote sensing images

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recommendations! Published in 2024 at "Remote Sensing Letters"

DOI: 10.1080/2150704x.2024.2377211

Abstract: ABSTRACT The fine-grained ship classification (FGSC) task in remote sensing aims to distinguish subordinate ship categories. Due to the high similarity among different subcategories and the significant variations in pose, scale, rotation, and color within… read more here.

Keywords: fine grained; remote sensing; grained ship; ship classification ... See more keywords

A New Benchmark and an Attribute-Guided Multilevel Feature Representation Network for Fine-Grained Ship Classification in Optical Remote Sensing Images

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recommendations! Published in 2020 at "IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing"

DOI: 10.1109/jstars.2020.2981686

Abstract: Maritime activities are essential aspects of human society. Accurate classification of ships is vital for maritime surveillance and meaningful to numerous civil and military applications. However, most studies conducted are limited to the coarse-grained ship… read more here.

Keywords: feature representation; attribute; ship classification; fine grained ... See more keywords

Multigranularity Self-Attention Network for Fine-Grained Ship Detection in Remote Sensing Images

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recommendations! Published in 2022 at "IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing"

DOI: 10.1109/jstars.2022.3220503

Abstract: Fine-grained ship detection is very important in the remote sensing field. Most previous remote sensing object detection works only utilize the global features for fine-grained object detection, which ignores the local information, deteriorating the detection… read more here.

Keywords: remote sensing; self attention; grained ship; detection ... See more keywords

Fine-Grained Ship Detection in High-Resolution Satellite Images With Shape-Aware Feature Learning

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recommendations! Published in 2023 at "IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing"

DOI: 10.1109/jstars.2023.3241969

Abstract: Fine-grained ship detection is an important task in high-resolution satellite remote sensing applications. However, large aspect ratios and severe category imbalance make fine-grained ship detection a challenging problem. Current methods usually extract square-like features that… read more here.

Keywords: grained ship; high resolution; detection; fine grained ... See more keywords

Fine-Grained Ship Recognition for Complex Background Based on Global to Local and Progressive Learning

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recommendations! Published in 2022 at "IEEE Geoscience and Remote Sensing Letters"

DOI: 10.1109/lgrs.2022.3168800

Abstract: The existing deep learning fine-grained recognition models have low recognition accuracy (Acc) in complex natural environments. We propose a fine-grained ship recognition model [global to local progressive learning module (GLPM)] based on global to local… read more here.

Keywords: recognition; grained ship; ship recognition; fine grained ... See more keywords

Few-Shot Fine-Grained Ship Classification With a Foreground-Aware Feature Map Reconstruction Network

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recommendations! Published in 2022 at "IEEE Transactions on Geoscience and Remote Sensing"

DOI: 10.1109/tgrs.2022.3172223

Abstract: Fine-grained ship classification plays an important part in many military and civilian applications. However, it is often costly to obtain images of ships, making it difficult to procure large numbers of such images. This difficulty… read more here.

Keywords: classification; grained ship; ship classification; fine grained ... See more keywords

Efficient Prompt Tuning of Large Vision-Language Model for Fine-Grained Ship Classification

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recommendations! Published in 2024 at "IEEE Transactions on Geoscience and Remote Sensing"

DOI: 10.1109/tgrs.2024.3509721

Abstract: Remote-sensing fine-grained ship classification (RS-FGSC) poses a significant challenge due to the high similarity between classes and the limited availability of labeled data, limiting the effectiveness of traditional supervised classification methods. Recent advancements in large… read more here.

Keywords: classification; fine grained; prompt; grained ship ... See more keywords