Unsupervised Barcode Image Reconstruction Based on Knowledge Distillation
Abstract
References
Index Terms
- Unsupervised Barcode Image Reconstruction Based on Knowledge Distillation
Recommendations
Super-resolution guided knowledge distillation for low-resolution image classification
Highlights- We propose a novel SRKD framework to solve the low-resolution classification problem.
AbstractWith the development of deep convolutional neural networks, the high-resolution image classification has achieved excellent classification results. However, in natural scenes, low-resolution images are very common, such as images taken ...
Multi-priors Guided Dehazing Network Based on Knowledge Distillation
Pattern Recognition and Computer VisionAbstractSingle image dehazing is a key prerequisite of high-level computer vision tasks since degraded images seriously affect the recognition ability of computers. Traditional prior-based methods conduct favorable dehazing effect but tend to cause ...
Unsupervised real image super-resolution via knowledge distillation network
AbstractSuper-resolution convolutional neural networks recently have demonstrated high-quality restoration for single images. Despite existing methods have achieved remarkable performance based on synthetic datasets, the performance is poor on real-world ...
Highlights- An unsupervised learning SR network is proposed: USRKDN.
- A degradation module is proposed to estimate the degradation kernel.
- A knowledge distillation module is proposed to transfer the learned mapping.
Comments
Information & Contributors
Information
Published In
![cover image ACM Other conferences](/cms/asset/305d8ab1-2ebb-41a3-8720-32f20cfba0e6/3503047.cover.jpg)
Publisher
Association for Computing Machinery
New York, NY, United States
Publication History
Check for updates
Author Tags
Qualifiers
- Research-article
- Research
- Refereed limited
Funding Sources
- Program for the Top Young Talents of Beijing High-level Innovation and Entrepreneurship
Conference
Acceptance Rates
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 93Total Downloads
- Downloads (Last 12 months)16
- Downloads (Last 6 weeks)1
Other Metrics
Citations
View Options
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign inFull Access
View options
View or Download as a PDF file.
PDFeReader
View online with eReader.
eReaderHTML Format
View this article in HTML Format.
HTML Format