What is he best known for?
The fields of study he is best known for:
- Quantum mechanics
- Algorithm
- Cryptography
Nanrun Zhou mostly deals with Encryption, Algorithm, Compressed sensing, Matrix and Pixel.
His biological study spans a wide range of topics, including Mellin transform, Image and Optics.
His research in Image intersects with topics in Discrete sine transform and Discrete Fourier transform.
His works in Key space and Scrambling are all subjects of inquiry into Algorithm.
His work focuses on many connections between Compressed sensing and other disciplines, such as Nonlinear system, that overlap with his field of interest in Logistic map.
His Pixel study incorporates themes from Chaotic and Key.
His most cited work include:
- Novel image compression–encryption hybrid algorithm based on key-controlled measurement matrix in compressive sensing (201 citations)
- Novel image compression–encryption hybrid algorithm based on key-controlled measurement matrix in compressive sensing (201 citations)
- Image compression–encryption scheme based on hyper-chaotic system and 2D compressive sensing (198 citations)
What are the main themes of his work throughout his whole career to date?
His main research concerns Algorithm, Encryption, Quantum computer, Quantum and Computer network.
His Algorithm research is multidisciplinary, relying on both Pixel, Optics, Mellin transform, Logistic map and Matrix.
Nanrun Zhou has researched Encryption in several fields, including Image, Discrete cosine transform, Chaotic and Compressed sensing.
His Quantum computer research includes themes of Quantum cryptography, Quantum algorithm, Theoretical computer science and Computational complexity theory.
The study incorporates disciplines such as Protocol and Encoding in addition to Quantum.
His work deals with themes such as Computer security, Key, Relay, Quantum network and Quantum information science, which intersect with Computer network.
He most often published in these fields:
- Algorithm (70.13%)
- Encryption (65.58%)
- Quantum computer (25.97%)
What were the highlights of his more recent work (between 2019-2021)?
- Algorithm (70.13%)
- Encryption (65.58%)
- Quantum (22.73%)
In recent papers he was focusing on the following fields of study:
His primary scientific interests are in Algorithm, Encryption, Quantum, Key space and Quantum cryptography.
His research integrates issues of Quantum computer and k-nearest neighbors algorithm in his study of Algorithm.
His Encryption research is multidisciplinary, incorporating elements of Pixel, Mellin transform, Image and Scrambling.
His work in Quantum covers topics such as Computer network which are related to areas like Cluster, Qubit and Encoding.
His study explores the link between Key space and topics such as Logistic map that cross with problems in Grayscale and Ciphertext.
His work carried out in the field of Quantum cryptography brings together such families of science as Quantum gate, Hénon map, Wavelet transform and Compression.
Between 2019 and 2021, his most popular works were:
- Optical image encryption algorithm based on phase-truncated short-time fractional Fourier transform and hyper-chaotic system (48 citations)
- Nonlinear optical multi-image encryption scheme with two-dimensional linear canonical transform (34 citations)
- Multi-image compression-encryption scheme based on quaternion discrete fractional Hartley transform and improved pixel adaptive diffusion (23 citations)
In his most recent research, the most cited papers focused on:
- Quantum mechanics
- Algorithm
- Artificial intelligence
His scientific interests lie mostly in Algorithm, Encryption, Chaotic, Key space and Pixel.
His study brings together the fields of Matrix and Algorithm.
His study in Encryption is interdisciplinary in nature, drawing from both Matching, Image, Discrete cosine transform and Quaternion.
He combines subjects such as Ciphertext, Grayscale, Nonlinear system, Coding and Robustness with his study of Chaotic.
His studies deal with areas such as Logistic map and Contourlet as well as Key space.
His Pixel research is multidisciplinary, incorporating perspectives in Plaintext, Hartley transform, Scrambling and Cryptosystem.
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