Sozo Inoue

1.7k total citations
117 papers, 1.1k citations indexed

About

Sozo Inoue is a scholar working on Computer Vision and Pattern Recognition, Computer Networks and Communications and Artificial Intelligence. According to data from OpenAlex, Sozo Inoue has authored 117 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 71 papers in Computer Vision and Pattern Recognition, 23 papers in Computer Networks and Communications and 22 papers in Artificial Intelligence. Recurrent topics in Sozo Inoue's work include Context-Aware Activity Recognition Systems (68 papers), IoT and Edge/Fog Computing (16 papers) and Human Mobility and Location-Based Analysis (16 papers). Sozo Inoue is often cited by papers focused on Context-Aware Activity Recognition Systems (68 papers), IoT and Edge/Fog Computing (16 papers) and Human Mobility and Location-Based Analysis (16 papers). Sozo Inoue collaborates with scholars based in Japan, Bangladesh and United Kingdom. Sozo Inoue's co-authors include Takeshi Nishida, Tahera Hossain, Md Atiqur Rahman Ahad, Paula Lago, Hiroto Yasuura, Naonori Ueda, Tsuyoshi Okita, Naoki Nakashima, Yasunobu Nohara and Yuichi Hattori and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Access and Sensors.

In The Last Decade

Sozo Inoue

105 papers receiving 1.1k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Sozo Inoue Japan	17	697	296	284	255	171	117	1.1k
Le T. Nguyen United States	12	641 0.9×	368 1.2×	223 0.8×	254 1.0×	164 1.0×	22	1.1k
Nishkam Ravi United States	10	821 1.2×	240 0.8×	367 1.3×	331 1.3×	383 2.2×	17	1.3k
Pang Wu United States	10	554 0.8×	280 0.9×	184 0.6×	220 0.9×	85 0.5×	14	897
Henrik Blunck Denmark	14	529 0.8×	288 1.0×	240 0.8×	109 0.4×	330 1.9×	31	1.0k
Gwenn Englebienne Netherlands	18	1.2k 1.7×	485 1.6×	359 1.3×	248 1.0×	295 1.7×	57	1.7k
Shuji Hao Singapore	8	998 1.4×	511 1.7×	338 1.2×	424 1.7×	189 1.1×	12	1.5k
Abdenour Bouzouane Canada	21	714 1.0×	305 1.0×	326 1.1×	115 0.5×	402 2.4×	117	1.5k
David Bannach Germany	10	752 1.1×	269 0.9×	267 0.9×	221 0.9×	112 0.7×	22	934
Alessio Vecchio Italy	17	407 0.6×	179 0.6×	390 1.4×	306 1.2×	202 1.2×	71	995
Charissa Ann Ronao South Korea	4	845 1.2×	296 1.0×	354 1.2×	342 1.3×	134 0.8×	6	1.1k

Countries citing papers authored by Sozo Inoue

Since Specialization

Citations

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

Fields of papers citing papers by Sozo Inoue

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sozo Inoue

This figure shows the co-authorship network connecting the top 25 collaborators of Sozo Inoue. A scholar is included among the top collaborators of Sozo Inoue 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 Sozo Inoue. Sozo Inoue is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Inoue, Sozo, et al.. (2024). Relabeling for Indoor Localization Using Stationary Beacons in Nursing Care Facilities. Sensors. 24(2). 319–319. 3 indexed citations

Inoue, Sozo, et al.. (2024). Improved Evaluation Metrics for Sentence Suggestions in Nursing and Elderly Care Record Applications. Healthcare. 12(3). 367–367. 1 indexed citations

Maekawa, Takuya, et al.. (2024). Preliminary Investigation of Activity Prediction in Nursing Homes using Activity History with Erroneous Time Stamps. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 851–855.

Ahad, Md Atiqur Rahman, Sozo Inoue, Guillaume Lopez, & Tahera Hossain. (2024). Human Activity and Behavior Analysis. UEL Research Repository (University of East London).

Inoue, Sozo, et al.. (2024). Synthetic Skeleton Data Generation using Large Language Model for Nurse Activity Recognition. 493–499.

Inoue, Sozo, et al.. (2023). Optimizing Forecasted Activity Notifications with Reinforcement Learning. Sensors. 23(14). 6510–6510. 2 indexed citations

Kanai, Satoshi, et al.. (2023). Experience of Integrative Research among Nursing Science, Engineering, and Information Technology and Tactics for Global Standard. Journal of the Robotics Society of Japan. 41(4). 345–353.

Sarno, Riyanarto, Sozo Inoue, Shoffi Izza Sabilla, et al.. (2022). A New Approach for Detection of Viral Respiratory Infections Using E-nose Through Sweat from Armpit with Fully Connected Deep Network. International journal of intelligent engineering and systems. 15(2). 394–404. 3 indexed citations

Sarno, Riyanarto, Sozo Inoue, Shoffi Izza Sabilla, et al.. (2022). Detection of Infectious Respiratory Disease Through Sweat From Axillary Using an E-Nose With Stacked Deep Neural Network. IEEE Access. 10. 51285–51298. 13 indexed citations

10.

Ahad, Md Atiqur Rahman, Sozo Inoue, Daniel Roggen, & Kaori Fujinami. (2022). Sensor- and Video-Based Activity and Behavior Computing. Smart innovation, systems and technologies. 7 indexed citations

11.

Inoue, Sozo, et al.. (2021). Integrating a spoken dialogue system, nursing records, and activity data collection based on smartphones. Computer Methods and Programs in Biomedicine. 210. 106364–106364. 3 indexed citations

12.

Okita, Tsuyoshi, et al.. (2019). Evaluation of Transfer Learning for Human Activity Recognition Among Different Datasets. 854–859. 5 indexed citations

13.

Kawaguchi, Nobuo, Nobuhiko Nishio, Daniel Roggen, et al.. (2019). Human activity sensing: corpus and applications. CERN Document Server (European Organization for Nuclear Research). 1 indexed citations

14.

Lago, Paula, Tsuyoshi Okita, Shingo Takeda, & Sozo Inoue. (2018). Improving Sensor-based Activity Recognition Using Motion Capture as Additional Information. 118–121. 1 indexed citations

15.

Kawaguchi, Nobuo, Nobuhiko Nishio, Daniel Roggen, et al.. (2017). 5th Int. workshop on human activity sensing corpus and applications (HASCA). 530–536. 1 indexed citations

16.

Inoue, Sozo, Naonori Ueda, Yasunobu Nohara, & Naoki Nakashima. (2016). Understanding Nursing Activities with Long-term Mobile Activity Recognition with Big Dataset. Proceedings of the ISCIE International Symposium on Stochastic Systems Theory and its Applications. 2016(0). 1–11. 3 indexed citations

17.

Inoue, Sozo, Naonori Ueda, Yasunobu Nohara, & Naoki Nakashima. (2016). Recognizing and Understanding Nursing Activities for a Whole Day with a Big Dataset. Journal of Information Processing. 24(6). 853–866. 15 indexed citations

18.

Inoue, Sozo. (2016). Human Sensing with Wearable Sensors. Journal of Japan Society for Fuzzy Theory and Intelligent Informatics. 28(6). 170–186. 1 indexed citations

19.

Kato, Hirokazu, Sozo Inoue, K. Tsubouchi, et al.. (2010). A Science Cloud: OneSpaceNet. AGU Fall Meeting Abstracts. 2010.

20.

Inoue, Sozo, et al.. (2002). Toward the Digitally Named World with Security and Convenience Using RFID Tags. 7(2). 131–137. 3 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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