James J. Davis

782 citations
29 papers · 434 indexed · h-index 10
Topics
Advanced Neural Network Applications (8 papers)Parallel Computing and Optimization Techniques (8 papers)Adversarial Robustness in Machine Learning (5 papers)

In The Last Decade

James J. Davis

27 papers receiving 386 citations

Peers

James J. Davis
Comparison fields: 5 of 81
  • Electrical and Electronic Engineering 165
  • Computer Vision and Pattern Recognition 128
  • Artificial Intelligence 103
  • Hardware and Architecture 100
  • Sociology and Political Science 59
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Citations per field
00.5×12.4×
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Citations per year

Countries citing papers authored by James J. Davis

Since Specialization
Citations

This map shows the geographic impact of James J. Davis'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 James J. Davis with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites James J. Davis more than expected).

Fields of papers citing papers by James J. Davis

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by James J. Davis. 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 James J. Davis. The network helps show where James J. Davis may publish in the future.

Co-authorship network of co-authors of James J. Davis

This figure shows the co-authorship network connecting the top 25 collaborators of James J. Davis. A scholar is included among the top collaborators of James J. Davis 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 James J. Davis. James J. Davis 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
#WorkIndexed citations
1 6
2 2
3 8
4 31
5 8
6 41
7 15
8 50
9 32
10 8
11 4
12 4
13 11
14 35
15 6
16 2
17
Experimenting with Adult Second Language Learners: A Case with Spanish Language at Northwestern High School in Prince George's County, Maryland.
1
18 26
19
Foreign Language Study and Afro-Americans: An Annotated Bibliography, 1931-1988.
1
20
Readability Formulas and Schema Theory: A New Look at Predicting and Measuring the Difficulty of Foreign Language Tests.
1

About James J. Davis

James J. Davis is a scholar working on Hardware and Architecture, Computer Vision and Pattern Recognition and Artificial Intelligence, having authored 29 papers that have together received 434 indexed citations. Recurring topics across this work include Advanced Neural Network Applications (8 papers), Parallel Computing and Optimization Techniques (8 papers) and Adversarial Robustness in Machine Learning (5 papers). The work is most often cited by research in Hardware and Architecture (100 citations), Computer Vision and Pattern Recognition (128 citations) and Anthropology (44 citations). James J. Davis has collaborated with scholars based in United Kingdom, United States and China. Frequent co-authors include Bruce Kapferer, Peter Y. K. Cheung, Erwei Wang, George A. Constantinides, Paul Markham, Joshua M. Levine, Rongxuan Zhao, Ho-Cheung Ng, Edward Stott and Xinyu Niu. Their work appears in journals such as ACM Computing Surveys, Computer and IEEE Transactions on Computers.

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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