A 1-D CNN with novel multi-stage spectral attention mechanisms and adjustable class-balanced focal loss improves recognition accuracy on real ship-radiated noise datasets.
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2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2026 2representative citing papers
UFPR-VeSV is a new real-world dataset for fine-grained vehicle classification and automatic license plate recognition collected from Brazilian police cameras, with benchmarks demonstrating its difficulty and the value of joint task use.
citing papers explorer
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Modulation Feature Enhancement with a Multi-Stage Attention Network for Underwater Acoustic Target Recognition
A 1-D CNN with novel multi-stage spectral attention mechanisms and adjustable class-balanced focal loss improves recognition accuracy on real ship-radiated noise datasets.
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Toward Unified Fine-Grained Vehicle Classification and Automatic License Plate Recognition
UFPR-VeSV is a new real-world dataset for fine-grained vehicle classification and automatic license plate recognition collected from Brazilian police cameras, with benchmarks demonstrating its difficulty and the value of joint task use.