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Xiaogang Mao

dblp:02/2071 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 1997
—ORCID · none

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

Databases, data management, data science and information retrieval · 2Artificial intelligence and machine learning · 1

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.

Databases, data mining, and information retrieval
1 paper
Information retrieval · 100%
Network and information security
1 paper
Digital forensics and information hiding · 100%

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

TopicWeightPapersLastEvidence papers
Information retrieval › document processing
document analysis
0.011997
Modified Fractal Signature (MFS): A New Approach to Document Analysis for Automatic Knowledge Acquisition · IEEE Trans. Knowl. Data Eng. 1997
Information retrieval › document processing › document analysis
document layout analysis
0.011997
Modified Fractal Signature (MFS): A New Approach to Document Analysis for Automatic Knowledge Acquisition · IEEE Trans. Knowl. Data Eng. 1997

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

modified fractal signature · 0.0
YearPublicationVenuePosition
1997 Modified Fractal Signature (MFS): A New Approach to Document Analysis for Automatic Knowledge Acquisition
abstract
One of the key technologies related to knowledge and data engineering is the acquisition of knowledge and data in the development and utilization of information system and the strategies to capture new knowledge and data. Actually, millions of documents, including technical reports, government files, newspapers, books, magazines, letters, bank checks, etc., have to be processed every day, and knowledge has to be acquired from them. This paper presents a new approach to document analysis for automatic knowledge acquisition. The traditional approaches have two major disadvantages: (1) They are not effective for processing documents with high geometrical complexity. Specially, the top-down approach can process only the simple documents which have specific format or contain some a priori information. (2) The top-down approach needs to split large components into small ones iteratively, while the bottom-up approach needs to merge small components into large ones iteratively. They are time consuming. This new approach is based on modified fractal signature. It can overcome the above weaknesses.
Yuan Yan Tang, Hong Ma 0001, Dihua Xi, Xiaogang Mao, Ching Y. Suen
IEEE Trans. Knowl. Data Eng.4
1995 A new approach to document analysis based on modified fractal signature
abstract
This paper presents a new approach to document analysis. The proposed approach is based on modified fractal signature. Instead of the time-consuming traditional approaches (top-down and bottom-up approaches) where iterative operations are necessary to break a document into blocks to extract its geometric (layout) structure, this new approach can divide a document into blocks in only one step. This approach can be used to process documents with high geometrical complexity. Experiments have been conducted to prove the proposed new approach for document processing.
Yuan Yan Tang, Hong Ma 0001, Xiaogang Mao, Ching Y. Suen
ICDAR3