Naoko Nitta

791 citations
59 papers · 420 indexed · h-index 11

Naoko Nitta

54 papers receiving 398 citations

Peers

Naoko Nitta
Comparison fields: 5 of 58
  • Computer Vision and Pattern Recognition 312
  • Signal Processing 155
  • Artificial Intelligence 106
  • Sociology and Political Science 93
  • Information Systems 41
Replace Erik Wijmans with:
Erik Wijmans United States
B.L. Tseng United States
Noel Murphy Ireland
Mayu Otani Japan
Eric Zavesky United States
Yousri Abdeljaoued Switzerland
Liang-Hua Chen Taiwan
Vamsidhar Reddy Gaddam Norway
B. Erol Canada
Regunathan Radhakrishnan United States
Naoko Nitta relative to Erik Wijmans United States Erik Wijmans's profile →
Citations per field
00.5×3.9×
Erik Wijmans · 1×
Citations per year

Countries citing papers authored by Naoko Nitta

Since Specialization
Citations

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

Fields of papers citing papers by Naoko Nitta

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Naoko Nitta, 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 Naoko Nitta Line = papers co-authored together Naoko Nitta links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20231
2 20222
3 202259
4 20211
5
Deep Face Recognizer Privacy Attack: Model Inversion Initialization by a Deep Generative Adversarial Data Space Discriminator
20204
6 20201
7 20194
8 20191
9 20173
10 20113
11
20090
12 200917
13 200842
14 20087
15
Human Identification in Surveillance Video Using RFID Tag and Camera Footage
20070
16
Viewing Interval Estimation for Personal Preference Acquisition in TV Viewing Environment
20061
17 20060
18 20052
19
Story Segmentation of Broadcasted Sports Videos for Semantic Content Acquisition
20032
20 200217

About Naoko Nitta

Naoko Nitta is a scholar working on Computer Vision and Pattern Recognition, Signal Processing and Geography, Planning and Development, having authored 59 papers that have together received 420 indexed citations. Recurring topics across this work include Video Analysis and Summarization (26 papers), Multimedia Communication and Technology (11 papers), Advanced Image and Video Retrieval Techniques (10 papers), Image Retrieval and Classification Techniques (10 papers), Music and Audio Processing (9 papers), Human Pose and Action Recognition (6 papers), Advanced Steganography and Watermarking Techniques (6 papers) and Video Surveillance and Tracking Methods (6 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (312 citations), Signal Processing (155 citations) and Artificial Intelligence (106 citations). Naoko Nitta has collaborated with scholars based in Japan, United States and Denmark. Frequent co-authors include Noboru Babaguchi, Kazuaki Nakamura, Yoshimasa Takahashi, Mahdi Khosravy, Xiaoyi Yu, Tadahiro Kitahashi, Guangzhen Li, Nilesh Patel, Neeraj Gupta and Nilanjan Dey. Their work appears in journals such as IEEE Access, IEEE Transactions on Information Forensics and Security and IEEE Transactions on Systems Man and Cybernetics Systems.

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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