Inkyu Sa

3.6k total citations · 1 hit paper
41 papers, 2.3k citations indexed

About

Inkyu Sa is a scholar working on Computer Vision and Pattern Recognition, Aerospace Engineering and Plant Science. According to data from OpenAlex, Inkyu Sa has authored 41 papers receiving a total of 2.3k indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Computer Vision and Pattern Recognition, 23 papers in Aerospace Engineering and 12 papers in Plant Science. Recurrent topics in Inkyu Sa's work include Robotics and Sensor-Based Localization (22 papers), Smart Agriculture and AI (11 papers) and Robotic Path Planning Algorithms (8 papers). Inkyu Sa is often cited by papers focused on Robotics and Sensor-Based Localization (22 papers), Smart Agriculture and AI (11 papers) and Robotic Path Planning Algorithms (8 papers). Inkyu Sa collaborates with scholars based in Australia, Switzerland and South Korea. Inkyu Sa's co-authors include Chris McCool, Tristán Pérez, Ben Upcroft, Feras Dayoub, Zongyuan Ge, Roland Siegwart, Juan Nieto, Zetao Chen, Marija Popović and Chris Lehnert and has published in prestigious journals such as Sensors, Remote Sensing and Autonomous Robots.

In The Last Decade

Inkyu Sa

39 papers receiving 2.2k citations

Hit Papers

DeepFruits: A Fruit Detection System Using Deep Neural Ne... 2016 2026 2019 2022 2016 250 500 750
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.

  1. DeepFruits: A Fruit Detection System Using Deep Neural Networks
    2016 807 citations Inkyu Sa, Zongyuan Ge et al. Sensors profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Inkyu Sa Australia 19 1.4k 647 500 448 386 41 2.3k
Chris McCool United States 28 1.8k 1.3× 826 1.3× 219 0.4× 402 0.9× 496 1.3× 99 3.5k
Xiangjun Zou China 38 2.7k 1.9× 944 1.5× 404 0.8× 347 0.8× 618 1.6× 141 4.1k
J. Hemming Netherlands 27 2.5k 1.8× 367 0.6× 255 0.5× 326 0.7× 304 0.8× 74 3.2k
Zize Liang China 24 807 0.6× 841 1.3× 303 0.6× 180 0.4× 249 0.6× 107 2.7k
Feras Dayoub Australia 18 1.1k 0.8× 1.5k 2.4× 1.0k 2.1× 289 0.6× 346 0.9× 55 3.1k
Lei Tian United States 25 917 0.7× 290 0.4× 232 0.5× 708 1.6× 245 0.6× 98 2.3k
John F. Reid United States 24 1.2k 0.9× 341 0.5× 195 0.4× 294 0.7× 278 0.7× 126 2.2k
Filipe Neves dos Santos Portugal 20 815 0.6× 358 0.6× 312 0.6× 188 0.4× 172 0.4× 102 1.4k
João Valente Netherlands 24 689 0.5× 586 0.9× 634 1.3× 442 1.0× 108 0.3× 89 2.0k
Lie Tang United States 31 1.3k 1.0× 262 0.4× 180 0.4× 576 1.3× 265 0.7× 111 2.7k

Countries citing papers authored by Inkyu Sa

Since Specialization
Citations

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

Fields of papers citing papers by Inkyu Sa

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Inkyu Sa

This figure shows the co-authorship network connecting the top 25 collaborators of Inkyu Sa. A scholar is included among the top collaborators of Inkyu Sa 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 Inkyu Sa. Inkyu Sa 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.
2.
Sa, Inkyu, et al.. (2024). MAVIS: Multi-Camera Augmented Visual-Inertial SLAM using SE2(3) Based Exact IMU Pre-integration. ANU Open Research (Australian National University). 1694–1700. 8 indexed citations
3.
4.
Borges, Paulo, Thierry Peynot, Inkyu Sa, et al.. (2022). A Survey on Terrain Traversability Analysis for Autonomous Ground Vehicles: Methods, Sensors, and Challenges. 2. 1567–1627. 50 indexed citations
5.
Lehnert, Chris, Chris McCool, Inkyu Sa, & Tristán Pérez. (2020). Performance improvements of a sweet pepper harvesting robot in protected cropping environments. Journal of Field Robotics. 37(7). 1197–1223. 76 indexed citations
6.
Kamel, Mina, Qixuan Zhang, Inkyu Sa, et al.. (2018). PaintCopter: An Autonomous UAV for Spray Painting on Three-Dimensional Surfaces. IEEE Robotics and Automation Letters. 3(4). 2862–2869. 40 indexed citations
7.
Reijgwart, Victor, Inkyu Sa, Renaud Dubé, et al.. (2018). Design of an Autonomous Racecar: Perception, State Estimation and System Integration. 2048–2055. 16 indexed citations
8.
Chen, Zetao, Lingqiao Liu, Inkyu Sa, Zongyuan Ge, & Margarita Chli. (2018). Learning Context Flexible Attention Model for Long-Term Visual Place Recognition. IEEE Robotics and Automation Letters. 3(4). 4015–4022. 64 indexed citations
9.
Popović, Marija, Teresa Vidal‐Calleja, Gregory Hitz, et al.. (2017). Multiresolution mapping and informative path planning for UAV-based terrain monitoring. 1382–1388. 43 indexed citations
10.
Sa, Inkyu, Chris Lehnert, Andrew English, et al.. (2017). Peduncle Detection of Sweet Pepper for Autonomous Crop Harvesting—Combined Color and 3-D Information. IEEE Robotics and Automation Letters. 2(2). 765–772. 93 indexed citations
11.
Lehnert, Chris, Inkyu Sa, Chris McCool, Ben Upcroft, & Tristán Pérez. (2016). Sweet pepper pose detection and grasping for automated crop harvesting. 2428–2434. 70 indexed citations
12.
McCool, Chris, Inkyu Sa, Feras Dayoub, et al.. (2016). Visual detection of occluded crop: For automated harvesting. 2506–2512. 61 indexed citations
13.
Sa, Inkyu, Chris McCool, Chris Lehnert, & Tristán Pérez. (2015). On Visual Detection of Highly-occluded Objects for Harvesting Automation in Horticulture. QUT ePrints (Queensland University of Technology). 7 indexed citations
14.
Pérez, Tristán, Inkyu Sa, Chris McCool, & Chris Lehnert. (2015). A Bayesian framework for the assessment of vision-based weed and fruit detection and classification algorithms. QUT ePrints (Queensland University of Technology). 2 indexed citations
15.
Sa, Inkyu, Stefan Hrabar, & Peter Corke. (2015). Inspection of Pole-Like Structures Using a Visual-Inertial Aided VTOL Platform with Shared Autonomy. Sensors. 15(9). 22003–22048. 16 indexed citations
16.
Sa, Inkyu, Stefan Hrabar, & Peter Corke. (2014). Inspection of pole-like structures using a vision-controlled VTOL UAV and shared autonomy. QUT ePrints (Queensland University of Technology). 3 indexed citations
17.
Sa, Inkyu & Peter Corke. (2013). Improved line tracker using IMU and Vision for visual servoing. QUT ePrints (Queensland University of Technology). 2 indexed citations
18.
Sa, Inkyu & Peter Corke. (2012). 100Hz onboard vision for quadrotor state estimation. QUT ePrints (Queensland University of Technology). 7 indexed citations
19.
Sa, Inkyu & Peter Corke. (2011). Estimation and control for an open-source quadcopter. QUT ePrints (Queensland University of Technology). 1 indexed citations
20.
Ahn, Ho Seok, et al.. (2008). Design of reconfigurable heterogeneous modular architecture for service robots. 1313–1318. 18 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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