James Smith

1.0k total citations
24 papers, 532 citations indexed

About

James Smith is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Public Health, Environmental and Occupational Health. According to data from OpenAlex, James Smith has authored 24 papers receiving a total of 532 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Artificial Intelligence, 9 papers in Computer Vision and Pattern Recognition and 2 papers in Public Health, Environmental and Occupational Health. Recurrent topics in James Smith's work include Domain Adaptation and Few-Shot Learning (9 papers), Multimodal Machine Learning Applications (7 papers) and Health and Medical Research Impacts (2 papers). James Smith is often cited by papers focused on Domain Adaptation and Few-Shot Learning (9 papers), Multimodal Machine Learning Applications (7 papers) and Health and Medical Research Impacts (2 papers). James Smith collaborates with scholars based in United States, Australia and France. James Smith's co-authors include Zsolt Kira, Yen-Chang Hsu, Bo Wu, Bogdan M. Wilamowski, Michael E. Baginski, Yilin Shen, Hongxia Jin, Leonid Karlinsky, Rogério Feris and Donghyun Kim and has published in prestigious journals such as Scientific Reports, Journal of the Atmospheric Sciences and IEEE Transactions on Antennas and Propagation.

In The Last Decade

James Smith

23 papers receiving 515 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
James Smith United States	11	262	148	65	52	49	24	532
Xiaoxuan Zhang China	14	75 0.3×	17 0.1×	31 0.5×	49 0.9×	177 3.6×	52	480
Georgios Kissas United States	4	72 0.3×	11 0.1×	22 0.3×	7 0.1×	23 0.5×	6	432
Guanqun Wang China	11	54 0.2×	223 1.5×	47 0.7×	11 0.2×	45 0.9×	63	526
Alessandro Sebastianelli Italy	7	138 0.5×	42 0.3×	36 0.6×	60 1.2×	17 0.3×	24	347
Carlos Almeida Portugal	12	88 0.3×	126 0.9×	6 0.1×	17 0.3×	26 0.5×	42	512
Wallace Casaca Brazil	14	89 0.3×	227 1.5×	36 0.6×	51 1.0×	42 0.9×	57	535
Thomas Skjødeberg Toftegaard Denmark	10	45 0.2×	102 0.7×	54 0.8×	70 1.3×	80 1.6×	38	536
Stefano Ubbiali Switzerland	3	40 0.2×	18 0.1×	137 2.1×	121 2.3×	29 0.6×	5	539
Paramate Horkaew Thailand	11	50 0.2×	80 0.5×	35 0.5×	117 2.3×	17 0.3×	48	367
Wenchao Chen China	12	59 0.2×	114 0.8×	10 0.2×	6 0.1×	21 0.4×	53	473

Countries citing papers authored by James Smith

Since Specialization

Citations

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

Fields of papers citing papers by James Smith

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of James Smith

This figure shows the co-authorship network connecting the top 25 collaborators of James Smith. A scholar is included among the top collaborators of James Smith 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 Smith. James Smith is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Smith, James, et al.. (2024). Man versus machine: cost and carbon emission savings of 4G-connected Artificial Intelligence technology for classifying species in camera trap images. Scientific Reports. 14(1). 14530–14530. 2 indexed citations

Smith, James, Yen-Chang Hsu, Zsolt Kira, Yilin Shen, & Hongxia Jin. (2024). Continual Diffusion with STAMINA: STack-And-Mask INcremental Adapters. 1744–1754. 1 indexed citations

Smith, James, et al.. (2024). Adaptive Memory Replay for Continual Learning. 3605–3615. 4 indexed citations

Alston, Laura, et al.. (2023). Creating a sustainable and supportive health research environment across rural and remote Australia: a call to action. The Medical Journal of Australia. 219(S3). S27–S30. 12 indexed citations

Smith, James. (2023). Tarski and Bachmann in Regina: A Magical Connection. Journal of Humanistic Mathematics. 13(2). 445–457.

Canuto, Kootsy, et al.. (2023). Further investment in Aboriginal and Torres Strait Islander men’s health research funding is urgently required. Australian and New Zealand Journal of Public Health. 47(2). 100025–100025. 1 indexed citations

Smith, James, Paola Cascante-Bonilla, Assaf Arbelle, et al.. (2023). ConStruct-VL: Data-Free Continual Structured VL Concepts Learning*. 14994–15004. 7 indexed citations

Smith, James, et al.. (2023). A Closer Look at Rehearsal-Free Continual Learning *. 2410–2420. 29 indexed citations

Cascante-Bonilla, Paola, James Smith, Donghyun Kim, et al.. (2023). Going Beyond Nouns With Vision & Language Models Using Synthetic Data. HAL (Le Centre pour la Communication Scientifique Directe). 20098–20108. 14 indexed citations

10.

Smith, James, Zachary Seymour, & Han-Pang Chiu. (2022). Incremental Learning with Differentiable Architecture and Forgetting Search. 2022 International Joint Conference on Neural Networks (IJCNN). 1–8. 2 indexed citations

11.

Smith, James, et al.. (2021). Memory-Efficient Semi-Supervised Continual Learning: The World is its Own Replay Buffer. 1–8. 17 indexed citations

12.

Smith, James, et al.. (2021). Always Be Dreaming: A New Approach for Data-Free Class-Incremental Learning. 2021 IEEE/CVF International Conference on Computer Vision (ICCV). 9354–9364. 89 indexed citations

13.

Smith, James & Michael E. Baginski. (2019). Thin-Wire Antenna Design Using a Novel Branching Scheme and Genetic Algorithm Optimization. IEEE Transactions on Antennas and Propagation. 67(5). 2934–2941. 32 indexed citations

14.

Wu, Bo, James Smith, Bogdan M. Wilamowski, & R.M. Nelms. (2018). DCMDS-RV: density-concentrated multi-dimensional scaling for relation visualization. Journal of Visualization. 22(2). 341–357. 1 indexed citations

15.

Lu, Ping, Ning Lin, Kerry Emanuel, Daniel R. Chavas, & James Smith. (2018). Assessing Hurricane Rainfall Mechanisms Using a Physics-Based Model: Hurricanes Isabel (2003) and Irene (2011). Journal of the Atmospheric Sciences. 75(7). 2337–2358. 59 indexed citations

16.

Schleiss, Marc & James Smith. (2015). A Method to Estimate the 3D–Time Structure of the Raindrop Size Distribution Using Radar and Disdrometer Data*. Journal of Hydrometeorology. 16(3). 1222–1242. 5 indexed citations

17.

Smith, James, et al.. (2011). Proceedings of the Anatomical Society of Great Britain and Ireland. Journal of Anatomy. 218(4). 462–470. 2 indexed citations

18.

Kerr, Debra, et al.. (2006). Predictors of ambulance use in patients with acute myocardial infarction in Australia. Emergency Medicine Journal. 23(12). 948–952. 38 indexed citations

19.

Smith, James. (2001). Summary of results - Joint NTGS - AGSO Age Determination Program 1999-2001. 38 indexed citations

20.

Smith, James. (2001). Practicing New Historicism. ISLE Interdisciplinary Studies in Literature and Environment. 8(2). 284–285. 10 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.

Explore authors with similar magnitude of impact