World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
44
Citations
7953
World Ranking
7586
National Ranking
998

Overview

Zhanyu Ma is affiliated with Beijing University of Posts and Telecommunications in China and has contributed extensively to the fields of computer science, particularly focusing on computer vision and pattern recognition.

Their main areas of study include:

  • Computer Vision and Pattern Recognition
  • Artificial Intelligence
  • Signal Processing
  • Radiology, Nuclear Medicine and Imaging
  • Cancer Research

Zhanyu Ma's research covers several core topics, such as:

  • Domain Adaptation and Few-Shot Learning
  • Multimodal Machine Learning Applications
  • Advanced Neural Network Applications
  • Advanced Image and Video Retrieval Techniques
  • Human Pose and Action Recognition
  • Video Surveillance and Tracking Methods
  • Anomaly Detection Techniques and Applications

The scientist has published papers mainly in venues including:

  • arXiv (Cornell University)
  • IEEE Transactions on Image Processing
  • Pattern Recognition
  • IEEE Transactions on Circuits and Systems for Video Technology
  • IEEE Transactions on Pattern Analysis and Machine Intelligence

Notable recent papers authored or coauthored by Zhanyu Ma include:

  • The Devil is in the Channels: Mutual-Channel Loss for Fine-Grained Image Classification, 2020, IEEE Transactions on Image Processing
  • BSNet: Bi-Similarity Network for Few-shot Fine-grained Image Classification, 2020, IEEE Transactions on Image Processing
  • Deep metric learning for few-shot image classification: A Review of recent developments, 2023, Pattern Recognition
  • A concise review of recent few-shot meta-learning methods, 2020, Neurocomputing
  • Duplex Contextual Relation Network For Polyp Segmentation, 2022, 2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI)

The frequent coauthors of Zhanyu Ma include:

  • Dongliang Chang
  • Kongming Liang
  • Jun Guo
  • Ruoyi Du
  • Xiaoxu Li

Zhanyu Ma has also contributed to book publications, particularly in collaboration with Springer Science+Business Media. The books are largely centered on pattern recognition and computer vision, with multiple editions published in 2023.

Best Publications

  • A Comprehensive Review of Smart Energy Meters in Intelligent Energy Networks

    Qie Sun;Hailong Li;Zhanyu Ma;Chao Wang

  • The Devil is in the Channels: Mutual-Channel Loss for Fine-Grained Image Classification

    Dongliang Chang;Yifeng Ding;Jiyang Xie;Ayan Kumar Bhunia

  • Fine-Grained Visual Classification via Progressive Multi-granularity Training of Jigsaw Patches

    Ruoyi Du;Dongliang Chang;Ayan Kumar Bhunia;Jiyang Xie

  • Dual Graph Convolutional Networks for Aspect-based Sentiment Analysis

    Ruifan Li;Hao Chen;Fangxiang Feng;Zhanyu Ma

  • Prediction of short-term PV power output and uncertainty analysis

    Luyao Liu;Yi Zhao;Dongliang Chang;Jiyang Xie

  • Knowledge-Driven Service Offloading Decision for Vehicular Edge Computing: A Deep Reinforcement Learning Approach

    Qi Qi;Jingyu Wang;Zhanyu Ma;Haifeng Sun

  • Bayesian Estimation of Beta Mixture Models with Variational Inference

    Zhanyu Ma;A. Leijon

  • Deep metric learning for few-shot image classification: A Review of recent developments

    Unknown

  • BSNet: Bi-Similarity Network for Few-shot Fine-grained Image Classification

    Xiaoxu Li;Jijie Wu;Zhuo Sun;Zhanyu Ma

  • Dual Cross-Entropy Loss for Small-Sample Fine-Grained Vehicle Classification

    Xiaoxu Li;Liyun Yu;Dongliang Chang;Zhanyu Ma

  • The Role of Data Analysis in the Development of Intelligent Energy Networks

    Zhanyu Ma;Jiyang Xie;Hailong Li;Qie Sun

  • AP-CNN: Weakly Supervised Attention Pyramid Convolutional Neural Network for Fine-Grained Visual Classification

    Yifeng Ding;Zhanyu Ma;Shaoguo Wen;Jiyang Xie

  • Variational Bayesian Matrix Factorization for Bounded Support Data

    Zhanyu Ma;Andrew E. Teschendorff;Arne Leijon;Yuanyuan Qiao

  • SketchMate: Deep Hashing for Million-Scale Human Sketch Retrieval

    Peng Xu;Yongye Huang;Tongtong Yuan;Kaiyue Pang

  • Fine-Grained Vehicle Classification With Channel Max Pooling Modified CNNs

    Zhanyu Ma;Dongliang Chang;Jiyang Xie;Yifeng Ding

  • A concise review of recent few-shot meta-learning methods

    Xiaoxu Li;Zhuo Sun;Jing-Hao Xue;Zhanyu Ma

  • Decorrelation of Neutral Vector Variables: Theory and Applications

    Zhanyu Ma;Jing-Hao Xue;Arne Leijon;Zheng-Hua Tan

  • Bayesian estimation of Dirichlet mixture model with variational inference

    Zhanyu Ma;Pravin Kumar Rana;Jalil Taghia;Markus Flierl

  • Fine-Grained Age Estimation in the Wild With Attention LSTM Networks

    Ke Zhang;Na Liu;Xingfang Yuan;Xinyao Guo

  • Your “Flamingo” is My “Bird”: Fine-Grained, or Not

    Dongliang Chang;Kaiyue Pang;Yixiao Zheng;Zhanyu Ma

  • Variational Bayesian Learning for Dirichlet Process Mixture of Inverted Dirichlet Distributions in Non-Gaussian Image Feature Modeling

    Zhanyu Ma;Yuping Lai;W. Bastiaan Kleijn;Yi-Zhe Song

  • Bayesian Estimation of the von-Mises Fisher Mixture Model with Variational Inference

    Jalil Taghia;Zhanyu Ma;Arne Leijon

Frequent Co-Authors

Jun Guo
Jun Guo Beijing University of Posts and Telecommunications
Jing-Hao Xue
Jing-Hao Xue University College London
Zheng-Hua Tan
Zheng-Hua Tan Aalborg University
Yi-Zhe Song
Yi-Zhe Song University of Surrey
Hailong Li
Hailong Li Mälardalen University
Liang Wang
Liang Wang Chinese Academy of Sciences
W. Bastiaan Kleijn
W. Bastiaan Kleijn Victoria University of Wellington
Jen-Tzung Chien
Jen-Tzung Chien National Yang Ming Chiao Tung University
Timothy M. Hospedales
Timothy M. Hospedales University of Edinburgh
Haibin Ling
Haibin Ling Westlake University

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

Exploring online education opens new doors for students interested in Computer Science and related fields. Prospective learners can benefit from affordable online colleges, which make quality education more accessible to a wider audience. These programs help reduce financial barriers, making it easier for students to pursue their ambitions without excessive debt.

Not every student has a perfect academic history. Fortunately, there are online colleges that accept low gpa, allowing motivated individuals the opportunity to prove themselves and excel in their chosen field.

For those seeking rapid progression, computer science degree online options—especially accelerated programs—enable learners to complete their studies quickly and enter the workforce sooner.

Additionally, if you're interested in interdisciplinary career options, it's worth exploring what fields are available. For example, by checking what can you do with an environmental science degree, you'll find a wide range of tech-driven and sustainability-focused careers to consider alongside Computer Science pathways.

Best Scientists Citing Zhanyu Ma

Trending Scientists

Recently Published Articles