Naresh Marturi

1.1k total citations
40 papers, 731 citations indexed

About

Naresh Marturi is a scholar working on Computer Vision and Pattern Recognition, Control and Systems Engineering and Media Technology. According to data from OpenAlex, Naresh Marturi has authored 40 papers receiving a total of 731 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Computer Vision and Pattern Recognition, 19 papers in Control and Systems Engineering and 10 papers in Media Technology. Recurrent topics in Naresh Marturi's work include Robot Manipulation and Learning (12 papers), Robotic Mechanisms and Dynamics (9 papers) and Soft Robotics and Applications (8 papers). Naresh Marturi is often cited by papers focused on Robot Manipulation and Learning (12 papers), Robotic Mechanisms and Dynamics (9 papers) and Soft Robotics and Applications (8 papers). Naresh Marturi collaborates with scholars based in United Kingdom, China and France. Naresh Marturi's co-authors include Rustam Stolkin, Licheng Jiao, Yangyang Li, Ronghua Shang, Maxime Adjigble, Aleš Leonardis, Valerio Ortenzi, Alireza Rastegarpanah, Xiaoning Shen and Yasemin Bekiroglu and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and IEEE Transactions on Geoscience and Remote Sensing.

In The Last Decade

Naresh Marturi

39 papers receiving 705 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Naresh Marturi United Kingdom 16 271 218 147 119 116 40 731
Paulo Costa Portugal 14 397 1.5× 365 1.7× 142 1.0× 41 0.3× 128 1.1× 145 980
David W. Capson Canada 14 536 2.0× 74 0.3× 78 0.5× 133 1.1× 75 0.6× 80 877
Zhaoqi Wang China 12 561 2.1× 86 0.4× 61 0.4× 107 0.9× 180 1.6× 73 933
Fabien Moutarde France 17 503 1.9× 207 0.9× 74 0.5× 67 0.6× 137 1.2× 51 1.0k
Yigang Cen China 18 734 2.7× 73 0.3× 89 0.6× 178 1.5× 255 2.2× 114 1.1k
Wentao Liu China 18 438 1.6× 133 0.6× 166 1.1× 23 0.2× 180 1.6× 92 1.0k
R.M. Parkin United Kingdom 15 112 0.4× 247 1.1× 150 1.0× 90 0.8× 42 0.4× 61 750
Jen‐Hui Chuang Taiwan 17 807 3.0× 157 0.7× 43 0.3× 85 0.7× 90 0.8× 89 1.1k
Abduladhem A. Ali Iraq 12 168 0.6× 125 0.6× 66 0.4× 39 0.3× 49 0.4× 59 498
Kun Qian China 14 304 1.1× 71 0.3× 52 0.4× 139 1.2× 56 0.5× 66 556

Countries citing papers authored by Naresh Marturi

Since Specialization
Citations

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

Fields of papers citing papers by Naresh Marturi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Naresh Marturi

This figure shows the co-authorship network connecting the top 25 collaborators of Naresh Marturi. A scholar is included among the top collaborators of Naresh Marturi 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 Naresh Marturi. Naresh Marturi 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.
Stolkin, Rustam, et al.. (2024). Unsupervised learning-based approach for detecting 3D edges in depth maps. Scientific Reports. 14(1). 796–796. 3 indexed citations
2.
Tamadazte, Brahim, et al.. (2024). Task-Informed Grasping of Partially Observed Objects. IEEE Robotics and Automation Letters. 9(10). 8394–8401. 1 indexed citations
3.
Adjigble, Maxime, Rustam Stolkin, & Naresh Marturi. (2023). Haptic-Guided Assisted Telemanipulation Approach for Grasping Desired Objects from Heaps. University of Birmingham Research Portal (University of Birmingham). 4142–4149. 2 indexed citations
4.
Szewczyk, Jérôme, et al.. (2022). Shared Control Schemes for Middle Ear Surgery. Frontiers in Robotics and AI. 9. 824716–824716. 2 indexed citations
5.
Rastegarpanah, Alireza, et al.. (2021). Nut Unfastening by Robotic Surface Exploration. Robotics. 10(3). 107–107. 13 indexed citations
6.
Li, Yangyang, et al.. (2020). Anchor-Free Single Stage Detector in Remote Sensing Images Based on Multiscale Dense Path Aggregation Feature Pyramid Network. IEEE Access. 8. 63121–63133. 27 indexed citations
7.
Li, Yangyang, et al.. (2020). Parallel design of sparse deep belief network with multi-objective optimization. Information Sciences. 533. 24–42. 7 indexed citations
8.
Ortenzi, Valerio, et al.. (2020). The Grasp Strategy of a Robot Passer Influences Performance and Quality of the Robot-Human Object Handover. Frontiers in Robotics and AI. 7. 542406–542406. 17 indexed citations
9.
Ortenzi, Valerio, et al.. (2020). Path planning for mobile manipulator robots under non-holonomic and task constraints. University of Birmingham Research Portal (University of Birmingham). 6749–6756. 14 indexed citations
10.
Shang, Ronghua, Jiyu Zhang, Licheng Jiao, et al.. (2020). Multi-scale Adaptive Feature Fusion Network for Semantic Segmentation in Remote Sensing Images. Remote Sensing. 12(5). 872–872. 83 indexed citations
11.
Li, Yangyang, et al.. (2019). Application of Data Driven Optimization for Change Detection in Synthetic Aperture Radar Images. IEEE Access. 8. 11426–11436. 6 indexed citations
12.
Bekiroglu, Yasemin, Naresh Marturi, Máximo A. Roa, et al.. (2019). Benchmarking Protocol for Grasp Planning Algorithms. IEEE Robotics and Automation Letters. 5(2). 315–322. 24 indexed citations
13.
Li, Yangyang, et al.. (2019). Hyper-Parameter Optimization Using MARS Surrogate for Machine-Learning Algorithms. IEEE Transactions on Emerging Topics in Computational Intelligence. 4(3). 287–297. 18 indexed citations
14.
Chen, Yanqiao, Licheng Jiao, Yangyang Li, et al.. (2018). A Novel Semicoupled Projective Dictionary Pair Learning Method for PolSAR Image Classification. IEEE Transactions on Geoscience and Remote Sensing. 57(4). 2407–2418. 11 indexed citations
15.
Marturi, Naresh, Marek Kopicki, Alireza Rastegarpanah, et al.. (2018). Dynamic grasp and trajectory planning for moving objects. Autonomous Robots. 43(5). 1241–1256. 64 indexed citations
16.
Ortenzi, Valerio, et al.. (2018). Vision-Based Framework to Estimate Robot Configuration and Kinematic Constraints. IEEE/ASME Transactions on Mechatronics. 23(5). 2402–2412. 20 indexed citations
17.
Adjigble, Maxime, Naresh Marturi, Valerio Ortenzi, et al.. (2018). Model-free and learning-free grasping by Local Contact Moment matching. University of Birmingham Research Portal (University of Birmingham). 2933–2940. 26 indexed citations
18.
Shen, Xiaoning, Leandro L. Minku, Naresh Marturi, Yinan Guo, & Ying Han. (2017). A Q-learning-based memetic algorithm for multi-objective dynamic software project scheduling. Information Sciences. 428. 1–29. 80 indexed citations
19.
Marturi, Naresh, et al.. (2016). Visual Servoing-Based Depth-Estimation Technique for Manipulation Inside SEM. IEEE Transactions on Instrumentation and Measurement. 65(8). 1847–1855. 18 indexed citations
20.
Malti, Abed, et al.. (2012). Toward Fast Calibration of Global Drift in Scanning Electron Microscopes with Respect to Time and Magnification. International Journal of Optomechatronics. 6(1). 1–16. 7 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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