David Johnson

1.4k total citations
31 papers, 577 citations indexed

About

David Johnson is a scholar working on Pollution, Computer Vision and Pattern Recognition and Nutrition and Dietetics. According to data from OpenAlex, David Johnson has authored 31 papers receiving a total of 577 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Pollution, 5 papers in Computer Vision and Pattern Recognition and 5 papers in Nutrition and Dietetics. Recurrent topics in David Johnson's work include Selenium in Biological Systems (5 papers), Face and Expression Recognition (4 papers) and Heavy metals in environment (3 papers). David Johnson is often cited by papers focused on Selenium in Biological Systems (5 papers), Face and Expression Recognition (4 papers) and Heavy metals in environment (3 papers). David Johnson collaborates with scholars based in China and United States. David Johnson's co-authors include Jason J. Corso, Caiming Xiong, Huigang Liu, Yingping Huang, Dong Ren, Ruiping Li, Tao Xu, Yingping Huang, Yanfen Fang and Antonio Torralba and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, The Science of The Total Environment and Applied Catalysis B: Environmental.

In The Last Decade

David Johnson

30 papers receiving 555 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
David Johnson China 13 120 108 85 80 60 31 577
Yu Shen China 15 27 0.2× 95 0.9× 22 0.3× 88 1.1× 27 0.5× 79 849
Arijit Ghosh India 10 36 0.3× 55 0.5× 56 0.7× 28 0.3× 45 0.8× 55 419
Xinhua Zhao China 16 85 0.7× 33 0.3× 37 0.4× 24 0.3× 62 1.0× 132 900
Xiaohan Jiang China 20 35 0.3× 79 0.7× 32 0.4× 148 1.9× 148 2.5× 75 1.2k
Jiahui Zhang China 14 258 2.1× 117 1.1× 29 0.3× 92 1.1× 183 3.0× 66 1.1k
Ashwani Kumar Dubey India 17 125 1.0× 18 0.2× 91 1.1× 90 1.1× 34 0.6× 91 934
Ashkan Banan Iran 11 53 0.4× 46 0.4× 72 0.8× 50 0.6× 10 0.2× 19 752
Ruyi Liu China 18 253 2.1× 131 1.2× 45 0.5× 95 1.2× 16 0.3× 65 1.0k
Man Zhang China 17 440 3.7× 92 0.9× 35 0.4× 119 1.5× 16 0.3× 52 1.0k

Countries citing papers authored by David Johnson

Since Specialization
Citations

This map shows the geographic impact of David Johnson's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by David Johnson with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Johnson more than expected).

Fields of papers citing papers by David Johnson

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David Johnson. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by David Johnson. The network helps show where David Johnson may publish in the future.

Co-authorship network of co-authors of David Johnson

This figure shows the co-authorship network connecting the top 25 collaborators of David Johnson. A scholar is included among the top collaborators of David Johnson based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with David Johnson. David Johnson is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Hu, Shuang, et al.. (2023). The effect of polyvinyl chloride (PVC) color on biofilm development and biofilm-heavy metal chemodynamics in the aquatic environment. The Science of The Total Environment. 905. 166924–166924. 3 indexed citations
2.
Li, Ming, Yingping Huang, Kun Li, et al.. (2023). Enhancement of electrokinetic-phytoremediation by Ophiopogon japonicus: stimulation of electrokinetic on root system and improvement of polycyclic aromatic hydrocarbon degradation. Environmental Science and Pollution Research. 30(43). 97591–97600. 4 indexed citations
3.
Johnson, David, et al.. (2022). Assessing machine leaning algorithms on crop yield forecasts using functional covariates derived from remotely sensed data. Computers and Electronics in Agriculture. 194. 106704–106704. 12 indexed citations
4.
Huang, Yingping, Kun Li, Huigang Liu, et al.. (2021). Distribution, sources and risk assessment of PAHs in soil from the water level fluctuation zone of Xiangxi Bay, Three Gorges Reservoir. Environmental Geochemistry and Health. 44(8). 2615–2628. 11 indexed citations
5.
Li, Ruiping, et al.. (2020). Spatial distribution, risk assessment, and source identification of heavy metals in water from the Xiangxi River, Three Gorges Reservoir Region, China. Environmental Geochemistry and Health. 43(2). 915–930. 27 indexed citations
6.
Xu, Tao, Ruiping Li, David Johnson, et al.. (2020). Heavy metal accumulation and health risk assessment of crayfish collected from cultivated and uncultivated ponds in the Middle Reach of Yangtze River. The Science of The Total Environment. 739. 139963–139963. 85 indexed citations
7.
Wang, Li, David Johnson, & Yingzi Lin. (2020). Using EEG to detect driving fatigue based on common spatial pattern and support vector machine. TURKISH JOURNAL OF ELECTRICAL ENGINEERING & COMPUTER SCIENCES. 29(3). 1429–1444. 15 indexed citations
8.
Huang, Yingping, et al.. (2019). Selenium enhanced phytoremediation of diesel contaminated soil by Alternanthera philoxeroides. Ecotoxicology and Environmental Safety. 173. 347–352. 12 indexed citations
9.
Huang, Yingping, et al.. (2019). Effects of lead and cadmium on photosynthesis in Amaranthus spinosus and assessment of phytoremediation potential. International Journal of Phytoremediation. 21(10). 1041–1049. 24 indexed citations
10.
Fang, Yanfen, et al.. (2019). Catalytic hydrolysis of microcystin-LR peptides on the surface of naturally occurring minerals. Research on Chemical Intermediates. 46(2). 1141–1152. 4 indexed citations
11.
Liu, Huigang, et al.. (2019). Selenium enhances Conyza canadensis phytoremediation of polycyclic aromatic hydrocarbons in soil. Journal of Soils and Sediments. 19(6). 2823–2835. 9 indexed citations
12.
Song, Yizhi, et al.. (2018). Se enhanced phytoremediation of diesel in soil by Trifolium repens. Ecotoxicology and Environmental Safety. 154. 137–144. 12 indexed citations
13.
Hamilton, Lei, et al.. (2017). SegICP: Integrated deep semantic segmentation and pose estimation. arXiv (Cornell University). 5784–5789. 100 indexed citations
14.
Fang, Yanfen, Hongwei Yang, Wei Zhou, et al.. (2015). BiOBr photocatalyzed decarboxylation of glutamic acid: reaction rates, intermediates and mechanism. RSC Advances. 5(69). 55727–55730. 3 indexed citations
15.
Johnson, David, Caiming Xiong, & Jason J. Corso. (2015). Semi-Supervised Nonlinear Distance Metric Learning via Forests of Max-Margin Cluster Hierarchies. IEEE Transactions on Knowledge and Data Engineering. 28(4). 1035–1046. 22 indexed citations
16.
Jia, Manke, et al.. (2015). Degradation of organic pollutants in waters by a water-insoluble iron(III) Schiff base complex. Applied Catalysis A General. 505. 70–76. 10 indexed citations
17.
Xiong, Caiming, David Johnson, & Jason J. Corso. (2013). Efficient Max-Margin Metric Learning. 5 indexed citations
18.
Xiong, Caiming, David Johnson, & Jason J. Corso. (2013). Uncertainty reduction for active image clustering via a hybrid global-local uncertainty model. National Conference on Artificial Intelligence. 149–151. 1 indexed citations
19.
Johnson, David, Caiming Xiong, Jing Gao, & Jason J. Corso. (2013). Comprehensive cross-hierarchy cluster agreement evaluation. National Conference on Artificial Intelligence. 56–58. 2 indexed citations
20.
Johnson, David, et al.. (1983). Degradation of Fenprostalene in Aqueous Solution. Journal of Pharmaceutical Sciences. 72(8). 946–948. 3 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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