Tetsuya Shimamura

211 papers receiving 1.4k citations

Hit Papers

Facial Emotion Recognition Using Transfer Learning in the...2021202620222024202150100150

Peers

Tetsuya Shimamura
Comparison fields: 5 of 113
  • Signal Processing 694
  • Computer Vision and Pattern Recognition 477
  • Artificial Intelligence 470
  • Computational Mechanics 252
  • Experimental and Cognitive Psychology 189
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Citations per field
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Citations per year

Countries citing papers authored by Tetsuya Shimamura

Since Specialization
Citations

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

Fields of papers citing papers by Tetsuya Shimamura

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tetsuya Shimamura

This figure shows the co-authorship network connecting the top 25 collaborators of Tetsuya Shimamura. A scholar is included among the top collaborators of Tetsuya Shimamura 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 Tetsuya Shimamura. Tetsuya Shimamura 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
#WorkIndexed citations
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4 8
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Rural community perception of fuelwood usage by families living in Wassorola, Mali: Interview with women as main fuelwood collectors
1
10
A fundamental frequency extraction method based on windowless and normalized autocorrelation functions
3
11
Perceptually motivated bayesian estimators with generalized gamma distribution under speech presence probability
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12 4
13
Reciprocal interactions between carbon storage function and plant species diversity in a tropical peat swamp forest (The front of area studies)
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14
A New Method of Noise Variance Estimation from Low-Order Yule-Walker Equations
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15
Pitch synchronous addition and extension for linear predictive analysis of noisy speech
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16
Training Adaptive Equalization With Blind Algorithms
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Noise Estimation Using High Frequency Regions for Spectral Subtraction
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18 1
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Throughput Analysis of Go-back-N ARQ in Cascade Connecting Links
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20
On the Vertical Moving Behaviour of Chum Salmon Early Migratory Season off the Coast of Shiretoko Peninsula
3

About Tetsuya Shimamura

Tetsuya Shimamura is a scholar working on Signal Processing, Computational Mechanics and Computer Vision and Pattern Recognition, having authored 247 papers that have together received 1.6k indexed citations. Recurring topics across this work include Speech and Audio Processing (104 papers), Advanced Adaptive Filtering Techniques (78 papers) and Blind Source Separation Techniques (53 papers). The work is most often cited by research in Signal Processing (694 citations), Computer Vision and Pattern Recognition (477 citations) and Artificial Intelligence (470 citations). Tetsuya Shimamura has collaborated with scholars based in Japan, Bangladesh and United Kingdom. Frequent co-authors include Hayato Kobayashi, Pranab Kumar Dhar, M. A. H. Akhand, Md Abdus Samad Kamal, Nazmul Siddique, Shuvendu Roy, Ryunosuke Tateno, Naoko Tokuchi, Norikazu Yamanaka and Sheng Du. Their work appears in journals such as The Journal of the Acoustical Society of America, IEEE Access and IEEE Transactions on Communications.

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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