F. Kojima

1.2k citations
80 papers · 837 · h-index 16

Impact in

Papers in

F. Kojima

75 papers receiving 799 citations

Peers

F. Kojima
Comparison fields: 5 of 91
  • Pulmonary and Respiratory Medicine 334
  • Mathematical Physics 64
  • Control and Systems Engineering 96
  • Computer Vision and Pattern Recognition 85
  • Anesthesiology and Pain Medicine 16
Replace Tzung-Chi Huang with:
Tzung-Chi Huang Taiwan
Lixu Gu China
Massoud Zolgharni United Kingdom
Christian Vasseur France
Jean‐Marc Girault France
Floris Ernst Germany
Igor Peterlík Czechia
Yu Lu China
Samrat Goswami United States
Matthias John Germany
F. Kojima relative to Tzung-Chi Huang Taiwan Tzung-Chi Huang's profile →
Citations per field
00.5×10×16×
Tzung-Chi Huang · 1×
Citations per year

Countries citing papers authored by F. Kojima

Since Specialization
Citations

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

Fields of papers citing papers by F. Kojima

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside F. Kojima, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with F. Kojima Line = papers co-authored together F. Kojima links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 80 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201086
2 199064
3 201153
4 201845
5 200237
6 201436
7 200828
8 200727
9 201124
10 201323
11 201619
12 202019
13 200018
14 201417
15 200016
16 201415
17
肺葉切除術における外科的縁の獲得における仮想補助肺マッピングの効果【JST・京大機械翻訳】
201813
18 200313
19 200213
20 200212

About F. Kojima

F. Kojima is a scholar working on Artificial Intelligence, Pulmonary and Respiratory Medicine, Control and Systems Engineering, Computer Vision and Pattern Recognition and Mechanical Engineering, having authored 80 papers that have together received 837 indexed citations. Recurring topics across this work include Robotic Path Planning Algorithms (12 papers), Lung Cancer Diagnosis and Treatment (11 papers), Reinforcement Learning in Robotics (11 papers), Neural Networks and Applications (8 papers), Non-Destructive Testing Techniques (6 papers), Numerical methods in inverse problems (5 papers), Social Robot Interaction and HRI (5 papers) and Fuzzy Logic and Control Systems (5 papers). The work is most often cited by research in Pulmonary and Respiratory Medicine (334 citations), Mathematical Physics (64 citations), Control and Systems Engineering (96 citations), Computer Vision and Pattern Recognition (85 citations) and Anesthesiology and Pain Medicine (16 citations). F. Kojima has collaborated with scholars based in Japan, United States and Netherlands. Frequent co-authors include Naoyuki Kubota, Kazumichi Yamamoto, Toshio Fukuda, H. T. Banks, Yoshihiro Miyamoto, Naoko Imanishi, Akihiro Ohsumi, Tatsuo Nakamura, William P. Winfree and Yusuke Nojima. Their work appears in journals such as Journal of Thoracic and Cardiovascular Surgery, Interactive Cardiovascular and Thoracic Surgery, European Journal of Cardio-Thoracic Surgery, Surgical Endoscopy and The Annals of Thoracic Surgery.

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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