Yoshiko Kojima

2.5k total citations
75 papers, 1.4k citations indexed

About

Yoshiko Kojima is a scholar working on Computer Vision and Pattern Recognition, Neurology and Automotive Engineering. According to data from OpenAlex, Yoshiko Kojima has authored 75 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Computer Vision and Pattern Recognition, 24 papers in Neurology and 17 papers in Automotive Engineering. Recurrent topics in Yoshiko Kojima's work include Vestibular and auditory disorders (24 papers), Autonomous Vehicle Technology and Safety (16 papers) and Video Surveillance and Tracking Methods (15 papers). Yoshiko Kojima is often cited by papers focused on Vestibular and auditory disorders (24 papers), Autonomous Vehicle Technology and Safety (16 papers) and Video Surveillance and Tracking Methods (15 papers). Yoshiko Kojima collaborates with scholars based in Japan, United States and Switzerland. Yoshiko Kojima's co-authors include Robijanto Soetedjo, Albert F. Fuchs, Reza Shadmehr, David J. Herzfeld, Kaoru Yoshida, Yoshiki Iwamoto, Chunzhao Guo, Junichi MEGURO, Takashi Naito and Kiyosumi Kidono and has published in prestigious journals such as Nature, Proceedings of the National Academy of Sciences and Neuron.

In The Last Decade

Yoshiko Kojima

72 papers receiving 1.4k citations

Peers

Yoshiko Kojima

NEURO

CMN

Nobuki Murayama Japan

J.A.M. Van Gisbergen Netherlands

Douglas Tweed Canada

Gunnar Blohm Canada

I. P. Howard Canada

Mark Shelhamer United States

Gabriel M. Gauthier France

Jean‐Louis Vercher France

Claudia Hendrix United States

Paul R. MacNeilage United States

Nobuki Murayama Japan

Yoshiko Kojima

1.1k ×1.5

235 ×0.4

NEURO

166 ×0.9

172 ×1.0

CMN

177 ×1.0

Citations per year, relative to Yoshiko Kojima Yoshiko Kojima (= 1×) peers Nobuki Murayama

Countries citing papers authored by Yoshiko Kojima

Since Specialization

Citations

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

Fields of papers citing papers by Yoshiko Kojima

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yoshiko Kojima

This figure shows the co-authorship network connecting the top 25 collaborators of Yoshiko Kojima. A scholar is included among the top collaborators of Yoshiko Kojima 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 Yoshiko Kojima. Yoshiko Kojima 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

Wood, Heather, Mohamed Aboueisha, Tzu‐Cheg Kao, et al.. (2024). Cognition and saccadic eye movement performance are impaired in chronic rhinosinusitis. International Forum of Allergy & Rhinology. 14(7). 1206–1217. 1 indexed citations

Kojima, Yoshiko, et al.. (2024). Comparison of adaptation characteristics between visually and memory-guided saccades. Journal of Neurophysiology. 132(2). 335–346. 1 indexed citations

May, Paul J., Susan Warren, & Yoshiko Kojima. (2024). The superior colliculus projection upon the macaque inferior olive. Brain Structure and Function. 229(8). 1855–1871. 5 indexed citations

Sedaghat-Nejad, Ehsan, et al.. (2021). P-sort: an open-source software for cerebellar neurophysiology. Journal of Neurophysiology. 126(4). 1055–1075. 21 indexed citations

Herzfeld, David J., Yoshiko Kojima, Robijanto Soetedjo, & Reza Shadmehr. (2018). Encoding of error and learning to correct that error by the Purkinje cells of the cerebellum. Nature Neuroscience. 21(5). 736–743. 123 indexed citations

El-Shamayleh, Yasmine, Yoshiko Kojima, Robijanto Soetedjo, & Gregory D. Horwitz. (2017). Selective Optogenetic Control of Purkinje Cells in Monkey Cerebellum. Neuron. 95(1). 51–62.e4. 55 indexed citations

Kidono, Kiyosumi, et al.. (2013). Sparse FIND: A Novel Low Computational Cost Feature for Object Classification. Journal of the Japan Society for Precision Engineering. 79(11). 1063–1068. 3 indexed citations

Kojima, Yoshiko, et al.. (2012). Development of a Novel Integrated Positioning System “PRECISE” for ADAS Applications. 19th ITS World CongressERTICO - ITS EuropeEuropean CommissionITS AmericaITS Asia-Pacific. 67. 1 indexed citations

Deguchi, Daisuke, et al.. (2012). A study on a method for high-accuracy detection of a pedestrian holding an umbrella with generative learning. 112(197). 191–196. 1 indexed citations

10.

Noda, Masafumi, Tomokazu Takahashi, Daisuke Deguchi, et al.. (2011). Detection of Road Markings Recorded in In-Vehicle Camera Images by Using Position-Dependent Classifiers. IEEJ Transactions on Industry Applications. 131(4). 466–474. 2 indexed citations

11.

Kojima, Yoshiko, et al.. (2011). Accurate Positioning using Virtually Increased GPS Satellites taken from Past Driving -- Evaluation in Suburban and Urban Areas. IEICE Technical Report; IEICE Tech. Rep.. 111(219). 37–42. 1 indexed citations

12.

MEGURO, Junichi, et al.. (2011). Automotive positioning based on bundle adjustment of GPS raw data and vehicle trajectory. 2. 1005–1011. 6 indexed citations

13.

Kojima, Yoshiko, et al.. (2010). Proposal of Precise Positioning Method Based on Accumulated GPS Raw Data -- Basic study for a moving vehicle. IEICE Technical Report; IEICE Tech. Rep.. 110(150). 1–6. 2 indexed citations

14.

Kojima, Yoshiko, Robijanto Soetedjo, & Albert F. Fuchs. (2010). Changes in Simple Spike Activity of Some Purkinje Cells in the Oculomotor Vermis during Saccade Adaptation Are Appropriate to Participate in Motor Learning. Journal of Neuroscience. 30(10). 3715–3727. 65 indexed citations

15.

Noda, Masafumi, Tomokazu Takahashi, Ichiro Ide, et al.. (2009). Recognition of Road Markings from In-Vehicle Camera Images by a Generative Learning Method. Machine Vision and Applications. 514–517. 14 indexed citations

16.

Noda, Masafumi, Tomokazu Takahashi, Daisuke Deguchi, et al.. (2009). Ego-localization by Matching In-vehicle Camera Images with Aerial Image. IEICE Technical Report; IEICE Tech. Rep.. 109(306). 177–182. 2 indexed citations

17.

Soetedjo, Robijanto, Yoshiko Kojima, & Albert F. Fuchs. (2008). Complex Spike Activity in the Oculomotor Vermis of the Cerebellum: A Vectorial Error Signal for Saccade Motor Learning?. Journal of Neurophysiology. 100(4). 1949–1966. 87 indexed citations

18.

Takahashi, Tomokazu, et al.. (2007). Accurate Vehicle Localization and Traveling Lane Classification by Aligning Laser Scanner Data Sequences. IEICE technical report. Speech. 107(206). 17–22. 1 indexed citations

19.

Kojima, Yoshiko, Yoshiki Iwamoto, Farrel R. Robinson, Christopher Noto, & Kaoru Yoshida. (2007). Premotor Inhibitory Neurons Carry Signals Related to Saccade Adaptation in the Monkey. Journal of Neurophysiology. 99(1). 220–230. 28 indexed citations

20.

Kojima, Yoshiko. (2003). Storage and erasure of information about saccadic gain adaptation. Neuroscience Research. 46. 1 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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