Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data. A simulation from public publication records: the people listed were not invited and did not agree to review.
? Tutorial for this page

Dongsheng Yao

dblp:97/1978 · DBLP profile ↗
← Back
3ranked-venue papers
0as first author
1since 2021 · last 2021
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 2Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer graphics and multimedia
1 paper
Image and video processing · 56% Image and video coding · 44%

Topics — the 2 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Image and video processing › binary image processing
connected component labeling
0.012002
An Algorithm with Reduced Operations for Connected Components Detection in ITU-T Group 3/4 Coded Images · IEEE Trans. Pattern Anal. Mach. Intell. 2002
Image and video coding › document image compression
facsimile coding
0.012002
An Algorithm with Reduced Operations for Connected Components Detection in ITU-T Group 3/4 Coded Images · IEEE Trans. Pattern Anal. Mach. Intell. 2002

Methods — techniques the papers use, named apart from their topics

MH/MR/MMR decoding · 0.0
YearPublicationVenuePosition
2021 Boundary Information Aggregation and Adaptive Keypoint Combination Enhanced Object Detection
Dongsheng Yao, Panyue Chen
ICIG (1)2
2005 Document analysis by processing JBIG-encoded images
Emma E. Regentova, Shahram Latifi, De Chen, Kazem Taghva, Dongsheng Yao
Int. J. Document Anal. Recognit.5
2002 An Algorithm with Reduced Operations for Connected Components Detection in ITU-T Group 3/4 Coded Images
abstract
An algorithm, which performs connected components detection in the course of decoding ITU-T (former CCITT) facsimile Group 3/4, i.e., MH/MR/MMR compressed images is presented. New definitions of mode color and a new transition element are introduced that allow MR/MMR codes to analyze and derive information about connection of black runs in two adjacent scan lines in the course of decoding. The experiments on the standard set of eight CCITT documents have shown that, on the average, the complexity of direct processing of MR/MMR codes is lower by a factor of 20 and 2.5 than that for raster images and MH codes processing respectively. Data structures for image vector description are discussed.
Emma E. Regentova, Shahram Latifi, Shulan Deng, Dongsheng Yao
IEEE Trans. Pattern Anal. Mach. Intell.4