H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 34 Citations 5,012 190 World Ranking 6368 National Ranking 42

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Algorithm
  • Cryptography

His primary areas of study are Secret sharing, Visual cryptography, Image, Homomorphic secret sharing and Theoretical computer science. His work in Secret sharing is not limited to one particular discipline; it also encompasses Image sharing. The various areas that Ching-Nung Yang examines in his Visual cryptography study include Artificial intelligence, Computer vision, Contrast and Human visual system model.

His Image study incorporates themes from Cover, Pixel and Arithmetic. In Homomorphic secret sharing, he works on issues like Lossless compression, which are connected to Computation. Ching-Nung Yang works mostly in the field of Theoretical computer science, limiting it down to topics relating to Algorithm and, in certain cases, Rotation and Copy detection.

His most cited work include:

  • New visual secret sharing schemes using probabilistic method (350 citations)
  • Effective and Efficient Global Context Verification for Image Copy Detection (270 citations)
  • Improvements of image sharing with steganography and authentication (235 citations)

What are the main themes of his work throughout his whole career to date?

Ching-Nung Yang mainly focuses on Image, Algorithm, Secret sharing, Visual cryptography and Artificial intelligence. His work in the fields of Image, such as Image sharing, intersects with other areas such as Block Truncation Coding. His Algorithm research is multidisciplinary, incorporating perspectives in Information hiding, Steganography and Code.

His biological study spans a wide range of topics, including Image processing and Theoretical computer science. The concepts of his Visual cryptography study are interwoven with issues in Decoding methods, Arithmetic, Encryption and Human visual system model. His Artificial intelligence study combines topics in areas such as Computer vision and Pattern recognition.

He most often published in these fields:

  • Image (36.32%)
  • Algorithm (35.90%)
  • Secret sharing (28.63%)

What were the highlights of his more recent work (between 2018-2021)?

  • Image (36.32%)
  • Algorithm (35.90%)
  • Artificial intelligence (25.21%)

In recent papers he was focusing on the following fields of study:

His primary areas of investigation include Image, Algorithm, Artificial intelligence, Information hiding and Image sharing. His work carried out in the field of Image brings together such families of science as Cover, Visual cryptography and Shadow. To a larger extent, he studies Cryptography with the aim of understanding Visual cryptography.

His work deals with themes such as Image quality and Bitmap, which intersect with Algorithm. The study incorporates disciplines such as Real-time data, Computer vision and Pattern recognition in addition to Artificial intelligence. His research in Information hiding intersects with topics in Pixel and Hamming code.

Between 2018 and 2021, his most popular works were:

  • Enabling Semantic Search Based on Conceptual Graphs over Encrypted Outsourced Data (127 citations)
  • Enhanced embedding capacity for the SMSD-based data-hiding method (46 citations)
  • Thresholds Based Image Extraction Schemes in Big Data Environment in Intelligent Traffic Management (29 citations)

In his most recent research, the most cited papers focused on:

  • Artificial intelligence
  • Algorithm
  • Cryptography

Ching-Nung Yang mainly investigates Image, Image sharing, Algorithm, Authentication and Decoding methods. Ching-Nung Yang is doing genetic studies as part of his Computer vision and Artificial intelligence and Image sharing investigations. His research investigates the connection between Computer vision and topics such as Cover that intersect with problems in Parity bit and Steganography.

Algorithm connects with themes related to Pixel in his study. His Decoding methods study combines topics from a wide range of disciplines, such as Computer network, Encryption and Visual cryptography. His research in Visual cryptography focuses on subjects like Single image, which are connected to Cryptography.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Top Publications

New visual secret sharing schemes using probabilistic method

Ching-Nung Yang.
Pattern Recognition Letters (2004)

538 Citations

Improvements of image sharing with steganography and authentication

Ching-Nung Yang;Tse-Shih Chen;Kun Hsuan Yu;Chung-Chun Wang.
Journal of Systems and Software (2007)

362 Citations

Effective and Efficient Global Context Verification for Image Copy Detection

Zhili Zhou;Yunlong Wang;Q. M. Jonathan Wu;Ching-Nung Yang.
IEEE Transactions on Information Forensics and Security (2017)

339 Citations

New Colored Visual Secret Sharing Schemes

Ching-Nung Yang;Chi-Sung Laih.
Designs, Codes and Cryptography (2000)

190 Citations

Enabling Semantic Search Based on Conceptual Graphs over Encrypted Outsourced Data

Zhangjie Fu;Fengxiao Huang;Xingming Sun;Athanasios V. Vasilakos.
IEEE Transactions on Services Computing (2019)

168 Citations

Image secret sharing method with two-decoding-options: Lossless recovery and previewing capability

Ching-Nung Yang;Chuei-Bang Ciou.
Image and Vision Computing (2010)

128 Citations

Effective and Efficient Image Copy Detection with Resistance to Arbitrary Rotation

Zhili Zhou;Ching-Nung Yang;Beijing Chen;Xingming Sun.
IEICE Transactions on Information and Systems (2016)

128 Citations

Visual Cryptography and Secret Image Sharing

Stelvio Cimato;Ching-Nung Yang.
(2017)

121 Citations

Colored visual cryptography scheme based on additive color mixing

Ching-Nung Yang;Tse-Shih Chen.
Pattern Recognition (2008)

112 Citations

Aspect ratio invariant visual secret sharing schemes with minimum pixel expansion

Ching-Nung Yang;Tse-Shih Chen.
Pattern Recognition Letters (2005)

111 Citations

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking h-index is inferred from publications deemed to belong to the considered discipline.

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