H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 59 Citations 9,856 368 World Ranking 1661 National Ranking 65

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Computer vision
  • Statistics

Artificial intelligence, Computer vision, Point cloud, Remote sensing and Lidar are his primary areas of study. His research on Artificial intelligence often connects related areas such as Pattern recognition. As part of his studies on Computer vision, Jonathan Li often connects relevant subjects like Completeness.

His work in Point cloud addresses issues such as Object detection, which are connected to fields such as Information extraction. His study in Remote sensing is interdisciplinary in nature, drawing from both Line, Mobile mapping and Hydrological modelling. The study incorporates disciplines such as Dashboard, Line segment, Scale and Standard deviation in addition to Lidar.

His most cited work include:

  • Spectral–Spatial Residual Network for Hyperspectral Image Classification: A 3-D Deep Learning Framework (279 citations)
  • Using mobile laser scanning data for automated extraction of road markings (159 citations)
  • Using mobile laser scanning data for automated extraction of road markings (159 citations)

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

His main research concerns Artificial intelligence, Point cloud, Computer vision, Pattern recognition and Remote sensing. His study looks at the relationship between Artificial intelligence and topics such as Lidar, which overlap with Ranging. His studies in Point cloud integrate themes in fields like Object detection, Point, Robustness and Algorithm.

His research in Computer vision tackles topics such as Cluster analysis which are related to areas like Euclidean distance. His research in Pattern recognition intersects with topics in Contextual image classification, Pixel and Object. His Remote sensing study frequently draws connections between related disciplines such as Land cover.

He most often published in these fields:

  • Artificial intelligence (71.40%)
  • Point cloud (47.92%)
  • Computer vision (41.67%)

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

  • Artificial intelligence (71.40%)
  • Point cloud (47.92%)
  • Pattern recognition (27.08%)

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

Jonathan Li mainly focuses on Artificial intelligence, Point cloud, Pattern recognition, Deep learning and Lidar. His Computer vision research extends to Artificial intelligence, which is thematically connected. His Augmented reality study, which is part of a larger body of work in Computer vision, is frequently linked to Road surface, bridging the gap between disciplines.

In his research on the topic of Point cloud, Data mining is strongly related with Point. His Deep learning research incorporates elements of Object detection and Remote sensing. His Lidar research includes elements of Ranging and Multispectral image.

Between 2019 and 2021, his most popular works were:

  • A convolutional neural network approach for counting and geolocating citrus-trees in UAV multispectral imagery (29 citations)
  • Squeeze-and-Attention Networks for Semantic Segmentation (25 citations)
  • Generative Adversarial Networks and Conditional Random Fields for Hyperspectral Image Classification (22 citations)

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

  • Artificial intelligence
  • Statistics
  • Computer vision

Jonathan Li mainly investigates Artificial intelligence, Point cloud, Deep learning, Pattern recognition and Lidar. His Artificial intelligence study frequently involves adjacent topics like Point. His Point cloud study is concerned with the larger field of Computer vision.

While the research belongs to areas of Computer vision, Jonathan Li spends his time largely on the problem of Simultaneous localization and mapping, intersecting his research to questions surrounding Parking lot, GNSS applications, Word error rate and Global Positioning System. His Deep learning research includes themes of Object, Intelligent transportation system and Discriminative model. The various areas that Jonathan Li examines in his Lidar study include Calibration, Perspective, Ranging and Camera resectioning.

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

Spectral–Spatial Residual Network for Hyperspectral Image Classification: A 3-D Deep Learning Framework

Zilong Zhong;Jonathan Li;Zhiming Luo;Michael Chapman.
IEEE Transactions on Geoscience and Remote Sensing (2018)

379 Citations

A study on DEM-derived primary topographic attributes for hydrologic applications: Sensitivity to elevation data resolution

Simon Wu;Jonathan Li;G.H. Huang.
Applied Geography (2008)

231 Citations

Using mobile laser scanning data for automated extraction of road markings

Haiyan Guan;Jonathan Li;Jonathan Li;Yongtao Yu;Cheng Wang.
Isprs Journal of Photogrammetry and Remote Sensing (2014)

216 Citations

Semi-automated extraction and delineation of 3D roads of street scene from mobile laser scanning point clouds

Bisheng Yang;Lina Fang;Jonathan Li.
Isprs Journal of Photogrammetry and Remote Sensing (2013)

202 Citations

Fractional vegetation cover estimation in arid and semi-arid environments using HJ-1 satellite hyperspectral data

Xianfeng Zhang;Chunhua Liao;Jonathan Li;Quan Sun.
International Journal of Applied Earth Observation and Geoinformation (2013)

161 Citations

Semiautomated Extraction of Street Light Poles From Mobile LiDAR Point-Clouds

Yongtao Yu;Jonathan Li;Haiyan Guan;Cheng Wang.
IEEE Transactions on Geoscience and Remote Sensing (2015)

153 Citations

Automated Extraction of Road Markings from Mobile Lidar Point Clouds

Bisheng Yang;Lina Fang;Qingquan Li;Jonathan Li.
Photogrammetric Engineering and Remote Sensing (2012)

147 Citations

Advances in Mobile Mapping Technology

C. Vincent Tao;Jonathan Li.
(2009)

142 Citations

Use of mobile LiDAR in road information inventory: a review

Haiyan Guan;Jonathan Li;Shuang Cao;Yongtao Yu.
International Journal of Image and Data Fusion (2016)

131 Citations

Learning Hierarchical Features for Automated Extraction of Road Markings From 3-D Mobile LiDAR Point Clouds

Yongtao Yu;Jonathan Li;Haiyan Guan;Fukai Jia.
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (2015)

127 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.

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

Contact us

Top Scientists Citing Jonathan Li

Bisheng Yang

Bisheng Yang

Wuhan University

Publications: 24

Pedro Arias

Pedro Arias

Universidade de Vigo

Publications: 23

Liangpei Zhang

Liangpei Zhang

Wuhan University

Publications: 20

Juha Hyyppä

Juha Hyyppä

Finnish Geospatial Research Institute

Publications: 20

Licheng Jiao

Licheng Jiao

Xidian University

Publications: 19

Antero Kukko

Antero Kukko

Aalto University

Publications: 14

Shunlin Liang

Shunlin Liang

University of Maryland, College Park

Publications: 13

Ayman Habib

Ayman Habib

Purdue University West Lafayette

Publications: 12

Harri Kaartinen

Harri Kaartinen

University of Turku

Publications: 12

David A. Clausi

David A. Clausi

University of Waterloo

Publications: 12

Biswajeet Pradhan

Biswajeet Pradhan

University of Technology Sydney

Publications: 12

Sisi Zlatanova

Sisi Zlatanova

UNSW Sydney

Publications: 11

Devis Tuia

Devis Tuia

École Polytechnique Fédérale de Lausanne

Publications: 11

Qingquan Li

Qingquan Li

Shenzhen University

Publications: 11

Uwe Stilla

Uwe Stilla

Technical University of Munich

Publications: 10

Something went wrong. Please try again later.