MicroCharNet: Less is More for License Plate Character Detection
License plate character detection is a crucial component of intelligent transportation systems, where high accuracy and computational efficiency are required for real-time deployment. Although recent deep learning-based methods have substantially improved detection performance, many high-accuracy models rely on large-scale architectures that incur substantial computational overhead, limiting their applicability to resource-constrained devices. In this paper, we propose MicroCharNet, an ultra-lightweight model specifically designed for license plate character detection. The proposed architectur
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- PossiblePossibly related (embedding) · 50%Automatically redact PII in images with Amazon Nova →
- PossiblePossibly related (embedding) · 46%deepseek-ai/DeepSeek-OCR →
- LinkedLinked via arxiv author · 85%Huy Che →
“MicroCharNet: Less is More for License Plate Character Detection”
- LinkedLinked via arxiv author · 85%Dinh-Duy Phan →
“MicroCharNet: Less is More for License Plate Character Detection”
- LinkedLinked via arxiv author · 85%Duc-Lung Vu →
“MicroCharNet: Less is More for License Plate Character Detection”
- PossiblePossibly related (embedding) · 46%parkpow/deep-license-plate-recognition →
