H-Index & Metrics Best Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science D-index 31 Citations 4,705 247 World Ranking 7748 National Ranking 735

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Algorithm
  • Machine learning

His primary areas of study are Radical polymerization, Polymer chemistry, Polymerization, Exponential stability and Artificial neural network. His studies in Radical polymerization integrate themes in fields like Lectin, Biochemistry, Click chemistry and Glycan. His Polymer chemistry study combines topics in areas such as Copolymer, Acrylate, Monomer, Thiol and Photochemistry.

His Polymerization research focuses on Disproportionation and how it connects with Aqueous solution and Copper mediated. His Exponential stability study deals with Hopfield network intersecting with Equilibrium point and Topology. His work deals with themes such as Feature extraction, Wavelet transform, Convolutional neural network and Kernel, which intersect with Artificial neural network.

His most cited work include:

  • A novel color image encryption algorithm based on DNA sequence operation and hyper-chaotic system (259 citations)
  • Image encryption using DNA addition combining with chaotic maps (252 citations)
  • Copper(II)/Tertiary Amine Synergy in Photoinduced Living Radical Polymerization: Accelerated Synthesis of ω-Functional and α,ω-Heterofunctional Poly(acrylates) (229 citations)

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

His main research concerns Artificial intelligence, Pattern recognition, Computer vision, Algorithm and Image. His studies in Feature, Convolutional neural network, Feature extraction, Motion capture and Synthetic aperture radar are all subfields of Artificial intelligence research. His study on Pattern recognition is mostly dedicated to connecting different topics, such as Facial recognition system.

His Algorithm research is multidisciplinary, incorporating elements of DNA and DNA sequencing. His Image research is multidisciplinary, relying on both Sequence and Encryption. The various areas that Qiang Zhang examines in his Encryption study include Pixel, Chaotic and Theoretical computer science.

He most often published in these fields:

  • Artificial intelligence (37.50%)
  • Pattern recognition (18.75%)
  • Computer vision (16.29%)

What were the highlights of his more recent work (between 2019-2021)?

  • Artificial intelligence (37.50%)
  • Pattern recognition (18.75%)
  • Image (8.71%)

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

Artificial intelligence, Pattern recognition, Image, RGB color model and Feature are his primary areas of study. His Artificial intelligence research integrates issues from Alpha and Computer vision. His Pattern recognition study integrates concerns from other disciplines, such as Modality, Focus, Representation and Embedding.

His work carried out in the field of Image brings together such families of science as Dimension, Encryption and Statistical model. His Feature research also works with subjects such as

  • Network model most often made with reference to Segmentation,
  • Image segmentation and related Key,
  • Normalization, Normalization and Pixel most often made with reference to Contextual image classification. His work focuses on many connections between Pixel and other disciplines, such as Chaotic, that overlap with his field of interest in Robustness.

Between 2019 and 2021, his most popular works were:

  • RGB-T Salient Object Detection via Fusing Multi-Level CNN Features (17 citations)
  • Tabu Variable Neighborhood Search for Designing DNA Barcodes (17 citations)
  • Attention-Guided Hierarchical Structure Aggregation for Image Matting (15 citations)

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

  • Artificial intelligence
  • Algorithm
  • Machine learning

Artificial intelligence, Pattern recognition, Feature, Algorithm and Convolutional neural network are his primary areas of study. His research in Artificial intelligence focuses on subjects like Computer vision, which are connected to Key. His study looks at the relationship between Pattern recognition and fields such as Deep learning, as well as how they intersect with chemical problems.

His Algorithm research includes themes of Dna storage and Word error rate. His study explores the link between RGB color model and topics such as Feature learning that cross with problems in Image. The Image study combines topics in areas such as Chaotic, Lorenz system, Encryption and Permutation.

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.

Best Publications

Image encryption using DNA addition combining with chaotic maps

Qiang Zhang;Ling Guo;Xiaopeng Wei.
Mathematical and Computer Modelling (2010)

346 Citations

A novel color image encryption algorithm based on DNA sequence operation and hyper-chaotic system

Xiaopeng Wei;Ling Guo;Qiang Zhang;Jianxin Zhang.
Journal of Systems and Software (2012)

316 Citations

A RGB image encryption algorithm based on DNA encoding and chaos map

Lili Liu;Qiang Zhang;Xiaopeng Wei.
Computers & Electrical Engineering (2012)

258 Citations

Delay-dependent exponential stability of cellular neural networks with time-varying delays

Qiang Zhang;Xiaopeng Wei;Jin Xu.
Chaos Solitons & Fractals (2005)

242 Citations

A novel image fusion encryption algorithm based on DNA sequence operation and hyper-chaotic system

Qiang Zhang;Ling Guo;Xiaopeng Wei.
Optik (2013)

225 Citations

Global exponential stability of Hopfield neural networks with continuously distributed delays

Qiang Zhang;Xiaopeng Wei;Jin Xu.
Physics Letters A (2003)

132 Citations

Improved algorithm for image encryption based on DNA encoding and multi-chaotic maps

Qiang Zhang;Lili Liu;Xiaopeng Wei.
Aeu-international Journal of Electronics and Communications (2014)

127 Citations

Robust Multi-Focus Image Fusion Using Multi-Task Sparse Representation and Spatial Context

Qiang Zhang;Martin D. Levine.
IEEE Transactions on Image Processing (2016)

124 Citations

A Unified Energy Efficiency and Spectral Efficiency Tradeoff Metric in Wireless Networks

Lei Deng;Yun Rui;Peng Cheng;Jun Zhang.
IEEE Communications Letters (2013)

111 Citations

Classification of ECG signals based on 1D convolution neural network

Dan Li;Jianxin Zhang;Qiang Zhang;Xiaopeng Wei.
international conference on e-health networking, applications and services (2017)

109 Citations

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Best Scientists Citing Qiang Zhang

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Licheng Jiao

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Xin Yang

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Sun Yat-sen University

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Yushu Zhang

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Nanjing University of Aeronautics and Astronautics

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Ju H. Park

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Yong He

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Hong Wang

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