Koichi Shinoda

128 papers receiving 1.2k citations

Peers

Koichi Shinoda
Comparison fields: 5 of 86
  • Artificial Intelligence 989
  • Signal Processing 761
  • Computer Vision and Pattern Recognition 331
  • Experimental and Cognitive Psychology 168
  • Social Psychology 82
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Countries citing papers authored by Koichi Shinoda

Since Specialization
Citations

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

Fields of papers citing papers by Koichi Shinoda

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Koichi Shinoda

This figure shows the co-authorship network connecting the top 25 collaborators of Koichi Shinoda. A scholar is included among the top collaborators of Koichi Shinoda 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 Koichi Shinoda. Koichi Shinoda 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
1 10
2
Speech Paralinguistic Approach for Detecting Dementia Using Gated Convolutional Neural Network
13
3
Semantic Indexing for Large-Scale Video Retrieval
2
4
Experiments with Optical Properties of Skin on Fingers
4
5
Speaker Diarization Using Multi-Modal i-vectors
1
6
Combining Audio Features and Visual I-Vector @ MediaEval 2015 Multimodal Person Discovery in Broadcast TV
2
7
TokyoTech-Waseda at TRECVID 2014.
1
8
Efficient model training for HMM-based person identification by gait
2
9
Large Vocabrary Sign Language Recognition Based on Cheremes
1
10
Acoustic model training using committee-based active and semi-supervised learning for speech recognition
6
11
A video watermarking method to objects robust against various attacks
1
12
TokyoTech+Canon at TRECVID 2011
4
13
Surveillance Event Detection Using Local and Global Features
0
14
Noise robust speech recognition using spectral subtraction and F0 information extracted by Hough transform
4
15
Speaker Selection for Unsupervised Speaker Adaptation based on HMM Sufficient Statistics
1
16
TokyoTech's TRECVID2006 Notebook
1
17
Robust Acoustic Modeling for Speech Recognition
1
18 7
19
Hidden Markov Model for Automatic Transcription of MIDI Signals
3
20 2

About Koichi Shinoda

Koichi Shinoda is a scholar working on Signal Processing, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 136 papers that have together received 1.4k indexed citations. Recurring topics across this work include Speech Recognition and Synthesis (69 papers), Speech and Audio Processing (57 papers) and Music and Audio Processing (41 papers). The work is most often cited by research in Signal Processing (761 citations), Artificial Intelligence (989 citations) and Computer Vision and Pattern Recognition (331 citations). Koichi Shinoda has collaborated with scholars based in Japan, United States and Czechia. Frequent co-authors include Takao Watanabe, Nakamasa Inoue, Sadaoki Furui, Kuniaki Uto, Chin‐Hui Lee, Koji Iwano, Hilman F. Pardede, Ryan Price, Takafumi Koshinaka and Johan Rohdin. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Scientific Reports and IEEE Signal Processing Magazine.

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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