H-Index & Metrics Best Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science D-index 41 Citations 6,851 188 World Ranking 4330 National Ranking 399

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Machine learning
  • Statistics

The scientist’s investigation covers issues in Artificial intelligence, Remote sensing, Computer vision, Pattern recognition and Hyperspectral imaging. His work on Contextual image classification, Statistical classification, Feature extraction and Artificial immune system is typically connected to Antibody as part of general Artificial intelligence study, connecting several disciplines of science. The various areas that Yanfei Zhong examines in his Remote sensing study include Evolutionary computation, Pyramid, Pyramid and Cluster analysis.

The concepts of his Computer vision study are interwoven with issues in Classifier, Deep learning and Convolutional neural network. His research investigates the connection between Pattern recognition and topics such as Probabilistic logic that intersect with issues in Visual dictionary and Semantic interpretation. The Hyperspectral imaging study combines topics in areas such as Tobler's first law of geography and Spatial analysis.

His most cited work include:

  • AID: A Benchmark Data Set for Performance Evaluation of Aerial Scene Classification (519 citations)
  • AID: A Benchmark Dataset for Performance Evaluation of Aerial Scene Classification (201 citations)
  • Bag-of-Visual-Words Scene Classifier With Local and Global Features for High Spatial Resolution Remote Sensing Imagery (164 citations)

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

His primary scientific interests are in Artificial intelligence, Pattern recognition, Remote sensing, Hyperspectral imaging and Computer vision. Artificial intelligence is represented through his Deep learning, Feature extraction, Pixel, Contextual image classification and Image research. His Pattern recognition research incorporates themes from Spatial analysis and Feature.

He has included themes like Artificial neural network, Cluster analysis and Conditional random field in his Remote sensing study. His work on Endmember as part of general Hyperspectral imaging study is frequently linked to Sparse matrix, therefore connecting diverse disciplines of science. His studies in Computer vision integrate themes in fields like Statistical classification and Scale.

He most often published in these fields:

  • Artificial intelligence (69.29%)
  • Pattern recognition (47.72%)
  • Remote sensing (46.89%)

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

  • Artificial intelligence (69.29%)
  • Remote sensing (46.89%)
  • Pattern recognition (47.72%)

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

His primary areas of study are Artificial intelligence, Remote sensing, Pattern recognition, Hyperspectral imaging and Deep learning. His studies in Feature extraction, Pixel, Convolutional neural network, Image and Image resolution are all subfields of Artificial intelligence research. His Remote sensing study combines topics from a wide range of disciplines, such as Object and Conditional random field.

His Pattern recognition study combines topics in areas such as Redundancy and Data set. His work deals with themes such as Regularization, Noise reduction, Noise and Visualization, which intersect with Hyperspectral imaging. Yanfei Zhong has researched Scale in several fields, including Change detection and Computer vision.

Between 2019 and 2021, his most popular works were:

  • Exploiting Deep Features for Remote Sensing Image Retrieval: A Systematic Investigation (33 citations)
  • Multiobjective Hyperspectral Feature Selection Based on Discrete Sine Cosine Algorithm (11 citations)
  • A robust spectral-spatial approach to identifying heterogeneous crops using remote sensing imagery with high spectral and spatial resolutions (10 citations)

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

  • Artificial intelligence
  • Machine learning
  • Statistics

Yanfei Zhong mainly investigates Remote sensing, Hyperspectral imaging, Artificial intelligence, Pattern recognition and Geospatial analysis. His studies deal with areas such as Object, Feature extraction, Convolutional neural network and Conditional random field as well as Remote sensing. He combines subjects such as Spatial analysis, Filter, Pixel, Spectral clustering and Mutual information with his study of Hyperspectral imaging.

He studies Deep learning which is a part of Artificial intelligence. Yanfei Zhong interconnects Regularization, Redundancy and Curse of dimensionality in the investigation of issues within Pattern recognition. His Geospatial analysis study also includes fields such as

  • Image segmentation most often made with reference to Focus,
  • Benchmark and Semantic change most often made with reference to Scale.

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

AID: A Benchmark Data Set for Performance Evaluation of Aerial Scene Classification

Gui-Song Xia;Jingwen Hu;Fan Hu;Baoguang Shi.
IEEE Transactions on Geoscience and Remote Sensing (2017)

644 Citations

AID: A Benchmark Data Set for Performance Evaluation of Aerial Scene Classification

Gui-Song Xia;Jingwen Hu;Fan Hu;Baoguang Shi.
IEEE Transactions on Geoscience and Remote Sensing (2017)

462 Citations

Bag-of-Visual-Words Scene Classifier With Local and Global Features for High Spatial Resolution Remote Sensing Imagery

Qiqi Zhu;Yanfei Zhong;Bei Zhao;Gui-Song Xia.
IEEE Geoscience and Remote Sensing Letters (2016)

201 Citations

An unsupervised artificial immune classifier for multi/hyperspectral remote sensing imagery

Yanfei Zhong;Liangpei Zhang;Bo Huang;Pingxiang Li.
IEEE Transactions on Geoscience and Remote Sensing (2006)

189 Citations

Dimensionality Reduction Based on Clonal Selection for Hyperspectral Imagery

Liangpei Zhang;Yanfei Zhong;Bo Huang;Jianya Gong.
IEEE Transactions on Geoscience and Remote Sensing (2007)

187 Citations

A new sub-pixel mapping algorithm based on a BP neural network with an observation model

Liangpei Zhang;Ke Wu;Yanfei Zhong;Pingxiang Li.
Neurocomputing (2008)

168 Citations

An Adaptive Artificial Immune Network for Supervised Classification of Multi-/Hyperspectral Remote Sensing Imagery

Yanfei Zhong;Liangpei Zhang.
IEEE Transactions on Geoscience and Remote Sensing (2012)

165 Citations

Scene Classification Based on the Multifeature Fusion Probabilistic Topic Model for High Spatial Resolution Remote Sensing Imagery

Yanfei Zhong;Qiqi Zhu;Liangpei Zhang.
IEEE Transactions on Geoscience and Remote Sensing (2015)

159 Citations

Dirichlet-Derived Multiple Topic Scene Classification Model for High Spatial Resolution Remote Sensing Imagery

Bei Zhao;Yanfei Zhong;Gui-Song Xia;Liangpei Zhang.
IEEE Transactions on Geoscience and Remote Sensing (2016)

149 Citations

Pre-Trained AlexNet Architecture with Pyramid Pooling and Supervision for High Spatial Resolution Remote Sensing Image Scene Classification

Xiaobing Han;Yanfei Zhong;Liqin Cao;Liangpei Zhang.
Remote Sensing (2017)

146 Citations

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