Derek Rose

2.4k total citations · 2 hit papers
29 papers, 1.6k citations indexed

About

Derek Rose is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Signal Processing. According to data from OpenAlex, Derek Rose has authored 29 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Artificial Intelligence, 11 papers in Computer Vision and Pattern Recognition and 4 papers in Signal Processing. Recurrent topics in Derek Rose's work include Neural Networks and Applications (5 papers), Advanced Neural Network Applications (4 papers) and Neural dynamics and brain function (3 papers). Derek Rose is often cited by papers focused on Neural Networks and Applications (5 papers), Advanced Neural Network Applications (4 papers) and Neural dynamics and brain function (3 papers). Derek Rose collaborates with scholars based in United States, Australia and Chile. Derek Rose's co-authors include Thomas P. Karnowski, Itamar Arel, Steven R. Young, Robert M. Patton, Seung–Hwan Lim, Thomas E. Potok, Vincent Paquit, Nisha Srinivas, Hairong Qi and Travis Johnston and has published in prestigious journals such as Science, Nature Communications and SAE technical papers on CD-ROM/SAE technical paper series.

In The Last Decade

Derek Rose

29 papers receiving 1.5k citations

Hit Papers

Deep Machine Learning - A New Frontier in Artificial Inte... 2010 2026 2015 2020 2010 2015 250 500 750

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Derek Rose United States 12 635 442 161 133 118 29 1.6k
Rafał Scherer Poland 20 518 0.8× 460 1.0× 123 0.8× 165 1.2× 80 0.7× 103 1.4k
Michael Gray United States 4 768 1.2× 520 1.2× 134 0.8× 171 1.3× 167 1.4× 5 1.9k
Habiboulaye Amadou Boubacar France 3 798 1.3× 477 1.1× 162 1.0× 159 1.2× 68 0.6× 6 1.8k
Genevieve Orr United States 8 777 1.2× 550 1.2× 182 1.1× 185 1.4× 83 0.7× 26 1.7k
Adi Alhudhaif Saudi Arabia 27 630 1.0× 513 1.2× 222 1.4× 141 1.1× 142 1.2× 106 2.0k
Yudong Tao United States 13 622 1.0× 385 0.9× 133 0.8× 111 0.8× 50 0.4× 50 1.5k
Ard Oerlemans Netherlands 5 518 0.8× 688 1.6× 99 0.6× 96 0.7× 152 1.3× 12 1.8k
S. Maouche France 11 658 1.0× 392 0.9× 183 1.1× 149 1.1× 45 0.4× 40 1.5k
Lili Guo China 24 574 0.9× 300 0.7× 259 1.6× 260 2.0× 98 0.8× 158 1.9k

Countries citing papers authored by Derek Rose

Since Specialization
Citations

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

Fields of papers citing papers by Derek Rose

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Derek Rose

This figure shows the co-authorship network connecting the top 25 collaborators of Derek Rose. A scholar is included among the top collaborators of Derek Rose 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 Derek Rose. Derek Rose 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.
Chai, Chengping, et al.. (2025). PickerXL, A Large Deep Learning Model to Measure Arrival Times from Noisy Seismic Signals. Seismological Research Letters. 96(4). 2394–2404. 1 indexed citations
2.
Ziabari, Amirkoushyar, Derek Rose, Abbas Shirinifard, & David J. Solecki. (2024). YOLO2U-Net: Detection-guided 3D instance segmentation for microscopy. Pattern Recognition Letters. 181. 37–42. 3 indexed citations
3.
Rose, Derek, et al.. (2021). Localized Defect Detection from Spatially Mapped, In-Situ Process Data With Machine Learning. Frontiers in Mechanical Engineering. 7. 14 indexed citations
4.
Han, Seung Baek, Ji‐Eun Kim, Jay A. Blundon, et al.. (2020). Schizophrenia-related microdeletion causes defective ciliary motility and brain ventricle enlargement via microRNA-dependent mechanisms in mice. Nature Communications. 11(1). 912–912. 31 indexed citations
5.
Schuman, Catherine D., et al.. (2020). Low Size, Weight, and Power Neuromorphic Computing to Improve Combustion Engine Efficiency. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 1–8. 12 indexed citations
6.
Ziabari, Amirkoushyar, et al.. (2019). A Two-Tier Convolutional Neural Network for Combined Detection and Segmentation in Biological Imagery. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 1–5. 3 indexed citations
7.
Chae, Junghoon, Catherine D. Schuman, Steven R. Young, et al.. (2019). Visualization System for Evolutionary Neural Networks for Deep Learning. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 4498–4502. 1 indexed citations
8.
Blundon, Jay A., Brett J.W. Teubner, Amar K. Pani, et al.. (2017). Restoring auditory cortex plasticity in adult mice by restricting thalamic adenosine signaling. Science. 356(6345). 1352–1356. 32 indexed citations
9.
Young, Steven R., Derek Rose, Travis Johnston, et al.. (2017). Evolving Deep Networks Using HPC. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 1–7. 30 indexed citations
10.
Young, Steven R., Derek Rose, Thomas P. Karnowski, Seung–Hwan Lim, & Robert M. Patton. (2015). Optimizing deep learning hyper-parameters through an evolutionary algorithm. 1–5. 283 indexed citations breakdown →
11.
Arel, Itamar, Derek Rose, & Thomas P. Karnowski. (2010). Deep Machine Learning - A New Frontier in Artificial Intelligence Research [Research Frontier]. IEEE Computational Intelligence Magazine. 5(4). 13–18. 774 indexed citations breakdown →
12.
Rose, Derek, Itamar Arel, Thomas P. Karnowski, & Vincent Paquit. (2010). Applying deep-layered clustering to mammography image analytics. 1–4. 8 indexed citations
13.
Arel, Itamar, Derek Rose, & Thomas P. Karnowski. (2010). Deep Machine Learning—A New Frontier in Artificial Intelligence Research. 215 indexed citations
14.
Young, Steven R., Itamar Arel, Thomas P. Karnowski, & Derek Rose. (2010). A Fast and Stable Incremental Clustering Algorithm. 204–209. 33 indexed citations
15.
Rose, Derek, Itamar Arel, Thomas P. Karnowski, & Vincent Paquit. (2010). Applying deep-layered clustering to mammography image analytics. 4 indexed citations
16.
French, W. G., Derek Rose, Peter Kelly-Zion, & Christopher J. Pursell. (2008). Analysis of Evaporating Fuel Films Using Shadowgraph and Schlieren Imaging Techniques. SAE technical papers on CD-ROM/SAE technical paper series. 4 indexed citations
17.
Qi, Hairong, et al.. (2007). A Public Key Cryptographic Method for Denial of Service Mitigation in Wireless Sensor Networks. 91. 51–59. 11 indexed citations
18.
Elhanany, I., et al.. (2006). Self-certified public key generation on the intel mote 2 sensor network platform. 118–120. 7 indexed citations
19.
Rose, Derek, et al.. (2004). The impact of manual handling training on work place injuries: a 14 year audit. Australian Health Review. 27(2). 80–87. 8 indexed citations
20.
Thompson, David, Sonia Sharp, M. C. B. Ellis, & Derek Rose. (1994). Improving schools : establishing and integrating whole school behaviour policies. Medical Entomology and Zoology. 9 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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