DCC: Difference between revisions
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{{Event series | {{Event series | ||
| | |Acronym=DCC | ||
|Title=Data Compression Conference | |Title=Data Compression Conference | ||
|has CORE2017 Rank=A* | |has CORE2017 Rank=A* | ||
|Field=Computer science | |||
|acronym=DCC | |||
}} | }} | ||
The Data Compression Conference (DCC) is an international forum for current work on data compression and related applications. | |||
* Compression of specific types of data (text, images, video, etc.). | |||
* Compression in networking, communications, and storage. | |||
* Applications to bioinformatics. | |||
* Applications to mobile computing. | |||
* Applications to information retrieval. | |||
* Computational issues for compression related applications. | |||
* Inpainting-based compression, perceptual coding. | |||
* Compressed data structures. | |||
* Quantization theory, and vector quantization (VQ). | |||
* Joint source-channel coding. | |||
* Compression related standards. | |||
Both theoretical and experimental work are of interest. | |||
Revision as of 06:12, 2 March 2020
| DCC | |
|---|---|
Data Compression Conference
| |
Categories: Computer science
| |
| CORE Rank (2017): | A* |
| Avg. acceptance rate: | 0 |
| Avg. acceptance rate (last 5 years): | 0 |
| Table of Contents | |
Data Compression Conference (DCC) has an average acceptance rate of 0% (last 5 years 0%).
Events
The following events of the series DCC are currently known in this wiki:
Number of Submitted and Accepted Papers (Main Track)
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Acceptance Rate
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Locations
The Data Compression Conference (DCC) is an international forum for current work on data compression and related applications.
- Compression of specific types of data (text, images, video, etc.).
- Compression in networking, communications, and storage.
- Applications to bioinformatics.
- Applications to mobile computing.
- Applications to information retrieval.
- Computational issues for compression related applications.
- Inpainting-based compression, perceptual coding.
- Compressed data structures.
- Quantization theory, and vector quantization (VQ).
- Joint source-channel coding.
- Compression related standards.
Both theoretical and experimental work are of interest.