James Graham

8.3k total citations · 1 hit paper
59 papers, 5.6k citations indexed

About

James Graham is a scholar working on Artificial Intelligence, Cognitive Neuroscience and Computer Vision and Pattern Recognition. According to data from OpenAlex, James Graham has authored 59 papers receiving a total of 5.6k indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Artificial Intelligence, 11 papers in Cognitive Neuroscience and 9 papers in Computer Vision and Pattern Recognition. Recurrent topics in James Graham's work include Physical Unclonable Functions (PUFs) and Hardware Security (7 papers), Reinforcement Learning in Robotics (7 papers) and Medical Image Segmentation Techniques (6 papers). James Graham is often cited by papers focused on Physical Unclonable Functions (PUFs) and Hardware Security (7 papers), Reinforcement Learning in Robotics (7 papers) and Medical Image Segmentation Techniques (6 papers). James Graham collaborates with scholars based in United States, United Kingdom and Poland. James Graham's co-authors include Chris Taylor, D. H. Cooper, T.F. Cootes, Janusz A. Starzyk, Mitra Tavakoli, Georgios Ponirakis, Ioannis N. Petropoulos, Xin Chen, Hassan Fadavi and Mohammad A. Dabbah and has published in prestigious journals such as IEEE Transactions on Signal Processing, American Journal of Obstetrics and Gynecology and The Journal of the Acoustical Society of America.

In The Last Decade

James Graham

53 papers receiving 5.3k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Active Shape Models-Their Training and Application

1995 4.8k citations T.F. Cootes, Chris Taylor et al. Computer Vision and Image Understanding profile →

Peers

Countries citing papers authored by James Graham

Since Specialization

Citations

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

Fields of papers citing papers by James Graham

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of James Graham

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

All Works

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20 of 20 papers shown

#	Work	Indexed citations
1	A New Way to Detect Cyberattacks: Extracting Changes in Register Values From Radio-Frequency Side Channels 2019 ·IEEE Signal Processing Magazine ·(unknown), James Graham, (unknown), Rusty O. Baldwin, (unknown)	5
2	Track generation in semi-supervised learning of self-structured algorithm using noisy and sparse, visual, and infrared data 2018 ·(unknown), (unknown), James Graham	0
3	Applying self-structured data learning algorithm to aerial infrared and visual images 2017 ·Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE ·(unknown), (unknown), James Graham, Roman Ilin	0
4	Development of Functional Requirements for Cognitive Motivated Machines 2016 ·OhioLink ETD Center (Ohio Library and Information Network) ·James Graham	0
5	Needs, Pains, and Motivations in Autonomous Agents 2016 ·IEEE Transactions on Neural Networks and Learning Systems ·Janusz A. Starzyk, James Graham, (unknown)	6
6	Implementing a self-structuring data learning algorithm 2016 ·Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE ·James Graham, (unknown), (unknown)	4
7	Detecting low bone mineral density from dental radiographs: a mini-review 2015 ·Clinical cases in mineral and bone metabolism ·James Graham	4
8	A comparative study between motivated learning and reinforcement learning 2015 ·Journal of Media Literacy Education ·James Graham, Janusz A. Starzyk, Zhen Ni, Haibo He, (unknown), Ah‐Hwee Tan	2
9	Prediction of Implant Loss and Marginal Bone Loss by Analysis of Dental Panoramic Radiographs 2015 ·The International Journal of Oral & Maxillofacial Implants ·Joe Merheb, James Graham, Wim Coucke, M. G. Roberts, Marc Quirynen, Reinhilde Jacobs, Hugh Devlin	11
10	Image Texture in Dental Panoramic Radiographs as a Potential Biomarker of Osteoporosis 2013 ·IEEE Transactions on Biomedical Engineering ·M. G. Roberts, James Graham, Hugh Devlin	58
11	Repeatability of In Vivo Corneal Confocal Microscopy to Quantify Corneal Nerve Morphology 2012 ·Cornea ·Ioannis N. Petropoulos, (unknown), Philip B. Morgan, Hassan Fadavi, Omar Asghar, Uazman Alam, Georgios Ponirakis, Mohammad A. Dabbah, Xin Chen, James Graham, Mitra Tavakoli, Rayaz A. Malik	139
12	Motivated learning for the development of autonomous systems 2011 ·Cognitive Systems Research ·Janusz A. Starzyk, James Graham, (unknown), Ah‐Hwee Tan	18
13	Anomaly prediction in network traffic using adaptive Wiener filtering and ARMA modeling 2008 ·Conference proceedings/Conference proceedings - IEEE International Conference on Systems, Man, and Cybernetics ·Mehmet Çelenk, (unknown), James Graham, John O. Willis	14
14	EFFICIENT GENERATION OF REDUCTS AND DISCERNS FOR CLASSIFICATION 2007 ·OhioLink ETD Center (Ohio Library and Information Network) ·James Graham	0
15	2 Dimensional Electrophoresis Gel Registration Using Point Matching and Local Image-Based Refinement 2004 ·Mike Rogers, James Graham, Ruize Tong	4
16	Robust Active Shape Model Search for Medical Image Analysis 2002 ·Research Explorer (The University of Manchester) ·C. Paul Rogers, James Graham	5
17	Building and using flexible models incorporating grey-level information 2002 ·Ktisis at Cyprus University of Technology (Cyprus University of Technology) ·T.F. Cootes, Chris Taylor, Andreas Lanitis, D. H. Cooper, James Graham	44
18	Active Shape Models-Their Training and Application breakdown → 1995 ·Computer Vision and Image Understanding ·T.F. Cootes, Chris Taylor, D. H. Cooper, James Graham	4845
19	Language behavior of the mentally retarded: syntactic characteristics. 1971 ·PubMed ·James Graham, (unknown)	14
20	EEG Responses to Auditory Stimuli in Waking Children 1963 ·Journal of Speech and Hearing Research ·(unknown), James Graham	12

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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