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Deep learning feature extraction for target recognition and classification in underwater sonar images
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Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/978-3-540-49886-5openalex-snapshot
The Handbook of Sidescan Sonar
inferredcites →https://doi.org/10.1007/s11263-015-0816-yopenalex-snapshot
ImageNet Large Scale Visual Recognition Challenge
inferredcites →https://doi.org/10.1016/b978-0-240-80740-9.50068-4openalex-snapshot
Digital Image Processing
inferredcites →https://doi.org/10.1049/ic:20060079openalex-snapshot
Target recognition in synthetic aperture and high resolution sidescan sonar
inferredcites →https://doi.org/10.1109/cvpr.2005.177openalex-snapshot
Histograms of Oriented Gradients for Human Detection
inferredcites →https://doi.org/10.1109/cvpr.2015.7298594openalex-snapshot
Going deeper with convolutions
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Performance evaluation of texture measures with classification based on Kullback discrimination of distributions
inferredcites →https://doi.org/10.1109/tpami.2012.231openalex-snapshot
Learning Hierarchical Features for Scene Labeling
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Reducing the Dimensionality of Data with Neural Networks
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ImageNet classification with deep convolutional neural networks
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A Fast Learning Algorithm for Deep Belief Nets
inferredcites →https://doi.org/10.1561/2200000006openalex-snapshot
Learning Deep Architectures for AI
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Learning Deep Architectures for AI
inferredcites →https://doi.org/10.48550/arxiv.1409.1556openalex-snapshot
Very Deep Convolutional Networks for Large-Scale Image Recognition
inferredcites →https://doi.org/10.48550/arxiv.1412.6806openalex-snapshot
Striving for Simplicity: The All Convolutional Net
inferredcites →https://doi.org/10.7551/mitpress/7496.003.0016openalex-snapshot
Scaling Learning Algorithms toward AI
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Survey on Deep Learning Techniques Used for Classification of Underwater Sonar Images
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Object Classification in Underwater SONAR Images using Transfer Learning Based Ensemble Model
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Semantic Segmentation of Underwater Images using UNet architecture based Deep Convolutional Encoder Decoder Model
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Automatic Target Recognition for Mine Countermeasure Missions Using Forward-Looking Sonar Data
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