Ship classification based on convolutional neural networks

Ship classification based on convolutional neural networks

Ship classification in optical images has been challenged by the complexity of various ships, different imaging conditions, and limited labelled images. Traditional methods focus on extracting handcrafted features for classification, but often fails to design well-performed features for complex imag...

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Bibliographic Details
Main Authors: Li Zhenzhen, Zhao Baojun, Tang Linbo, Li Zhen, Feng Fan
Format: Article
Language:English
Published: Wiley 2019-10-01
Series:The Journal of Engineering
Subjects:
learning (artificial intelligence)
ships
image classification
feature extraction
convolutional neural nets
limited labelled images
different imaging conditions
optical images
convolutional neural networks
optical ship images
achieving good classification performance
supervised learning
ship classification approach
complex images
handcrafted features
traditional methods focus
Online Access:https://digital-library.theiet.org/content/journals/10.1049/joe.2019.0422

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https://digital-library.theiet.org/content/journals/10.1049/joe.2019.0422

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