研究者詳細 - 吉田　香

論文 - 吉田　香

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Enhancing Decision-Making System with Implicit Attitude and Preferences: A Comprehensive Review in Computational Social Science 査読有り国際誌

SILPANI Dian Christy, YOSHIDA Kaori

International Journal of Affective Engineering ( 日本感性工学会 ) advpub ( 0 ) 2024年01月

担当区分：最終著者記述言語：英語掲載種別：研究論文（学術雑誌）

Implicit attitudes and preferences can be dynamic and context-dependent, evolving over time and in different situations. In this study, we point out 4 main topics: Implicit attitudes, preferences, decision-making system, and computational social science, to introduce a new approach to developing a decision-making system. As a comprehensive review, we set the 3 research questions as the main considerations for this study. We collected 903,451 articles using 3 major database sources (ScienceDirect, ACM Digital Library, and IEEE Xplore), screened 5 times with different viewpoints, and surveyed 14 articles to answer the research questions. As a result of the comprehensive review, we conclude that it shows the possibility of enhancing the decision-making system with implicit attitudes and preferences in a computational social science manner.

DOI： 10.5057/ijae.ijae-d-24-00011

CiNii Research

The Impact of Large Sample Datasets on Hand Gesture Recognition by Hand Landmark Classification 査読有り国際誌

AHMAD Khawaritzmi Abdallah, SILPANI Dian Christy, YOSHIDA Kaori

International Journal of Affective Engineering ( 日本感性工学会 ) 22 ( 3 ) 253 - 259 2023年07月

担当区分：最終著者記述言語：英語掲載種別：研究論文（学術雑誌）

Today, almost all aspects of life are influenced by technology to simplify these aspects of life. Researching how humans and computers interact is very important to build a good model for better human-computer interaction in the future. Using technology such as computer vision, we can now collect the information we are looking for directly from a human. Humans can use many kinds of modalities to interact with computers. Hands are perhaps the largest source of body language information after the face. To understand the gesture’s meaning, we can use MediaPipe Hands, developed at Google LLC, as a method to track and recognize human hands. However, if we want to understand some kinds of hand gestures using MediaPipe Hands, we need to create a condition using if-else manners. This research tried to collect the wide variety of each hand gesture using the 21 key points in x, y, and z coordinates as a feature. We chose Support Vector Machine (SVM) and Artificial Neural Network (ANN) as classifiers to validate the impact of large sample datasets. This research found that ANN is the best among all the methods we used as a classifier method for the 3D value of 21 key points from the hand skeleton. The accuracy and F1-score from ANN were 98.4% accuracy and 98.2% F1-Score, respectively, representing the best performance for each class of all the methods we used in this research.

DOI： 10.5057/ijae.ijae-d-22-00022

CiNii Research

その他リンク： https://www.jstage.jst.go.jp/article/ijae/22/3/22_IJAE-D-22-00022/_pdf

STATIC HAND GESTURE RECOGNITION BASED ON MULTI-FEATURE EXTRACTION WITH CONTEXT FOR USER INTENSION 査読有り

Ahmad K.A., Silpani D.C., Yoshida K.

ICIC Express Letters, Part B: Applications ( ICIC International 学会 ) 15 ( 8 ) 779 - 786 2024年08月

担当区分：最終著者記述言語：英語掲載種別：研究論文（学術雑誌）

Hand gesture is a source of information that contains much information, which has the advantage that this modality does not contain private information as much as information obtained from facial modalities. However, obtaining information from hand gestures still encounters several challenges, one of which is the diversity of gestures within one target class which is influenced by many factors such as the culture and personality of the individual. In this study, we propose a method of combining hand gesture features in the form of keypoints features, convolutional neural network features, and manually generating captions as contexts to improve model performance so that the model can classify hand gestures based on the intent of the hand gesture with context support. As a result, the CNN model, which initially experienced over-fitting when trying to classify hand gestures based on the intent of the hand gesture, can be overcome by this method. Running results show a significant increase in accuracy over training models that just use uni-features, with a model having a training accuracy of 99.95% and a validation accuracy of 99.74%. The final result of the model obtained the ability to understand 6 classes of hand gestures made in 3 classes based on the intent of the hand gestures exhibited when participants try the taste of tea, namely Like, Dislike, and Neutral (So-so).

DOI： 10.24507/icicelb.15.08.779

Scopus

CiNii Research

その他リンク： https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85202546702&origin=inward

Static Hand Gesture Recognition based on Multi-Feature extraction with Context for User Intension 査読有り国際誌

(1) Khawaritzmi Abdallah Ahmad, Dian Christy Silpani and Kaori Yoshida

ICIC Express Letters, Part B: Applications 15 ( 8 ) 2024年08月

An Investigation of the Effects of Presentation Methods for Visual Elements and Thinking Styles on Text Comprehension 査読有り国際誌

Kouki Ueno, Kaori Yoshida and Naruki Shirahama

ICIC Express Letters, Part B: Applications 15 ( 6 ) 561 - 573 2024年06月

Implicit Attitude of Human Behavior: A Review 査読有り

Dian Christy Silpani and Kaori Yoshida

Proceedings of Computer Information Systems, Biometrics and Kansei Engineering 2023 102 - 114 2023年09月

Static Hand Gesture Recognition Based on Multi-Feature Extraction with Context for User Intension 査読有り国際誌

Khawaritzmi Abdallah Ahmad, Dian Christy Silpani and Kaori Yoshida

Proc. of 17th International Conference on Innovative Computing, Information and Control (ICICIC2023) ( 142 ) 2023年08月

An Investigation of the Effects of Presentation Methods for Visual Elements and Thinking Styles on Text Comprehension 査読有り国際誌

Kouki Ueno, Kaori Yoshida and Naruki Shirahama

Proc. of 17th International Conference on Innovative Computing, Information and Control (ICICIC2023) ( 125 ) 2023年08月

A Feasibility Study on Hand Gesture Intention Interpretation Based on Gesture Detection and Speech Recognition 査読有り国際誌

Silpani Dian Christy, Suematsu Keishi, Yoshida Kaori

Journal of Advanced Computational Intelligence and Intelligent Informatics ( 富士技術出版株式会社 ) 26 ( 3 ) 375 - 381 2022年05月

担当区分：最終著者記述言語：英語掲載種別：研究論文（学術雑誌）

In this paper, considering the characteristics of hand gestures that occur during a natural, unscripted human conversation, we report the results of experiments involving the data analysis of the video recordings of experiments. The recorded conversations between two subjects and the assistant in the experiments (the first author) are analyzed for findings that might be useful to future human-robot interaction (HRI), findings regarding the recognition of hand gestures in natural conversations. In the experiment, hand gestures that appeared naturally during the conversations were manually selected, and their elapsed times and number of appearances were analyzed. In addition, these unscripted conversations were analyzed with a voice recognition system, and the meanings of the hand gestures that appear in the recorded video were interpreted. It was observed that some gestures were made consciously and others unconsciously. Some gestures appeared multiple times with similar meanings and the same intention, especially gestures involving pointing at something to emphasize a sentence or word. Other observations included that there were times when (i) each subject made different hand gestures to convey the same meaning, (ii) both subjects made the same hand gesture but intended different meanings, and (iii) a specific gesture was made by the same subject but with different intended meanings. After considering the results of these experiments, we conclude that it is better to combine gestures with the utterances at the time in order to interpret their intended meanings correctly.

DOI： 10.20965/jaciii.2022.p0375

Scopus

CiNii Research

その他リンク： https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85132786254&origin=inward

Hand Gesture Recognition by Hand Landmark Classification 査読有り国際誌

AHMAD Khawaritzmi Abdallah, SILPANI Dian Christy, YOSHIDA Kaori

International Symposium on Affective Science and Engineering ( 日本感性工学会 ) ISASE2022 ( 0 ) 1 - 4 2022年01月

担当区分：最終著者記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

These years, computer vision technology has been rapidly advanced. On the other hand, customer satisfaction is essential for the industry to improve its service but use traditional methods ineffectively. Using technology such as computer vision, we can now collect the information we are looking for directly from a human. Humans can use many kinds of modalities to interact with computers. Hands are perhaps the largest source of body language information after the face. To understand the gesture's meaning, we can use MediaPipe Hands developed at Google LLC as a method to track and recognize human hands. However, if we want to understand some kinds of hand gestures using MediaPipe Hands, we need to create a condition ourselves by using if-else conditions. This research tried to collect the many varieties of each hand gesture using the 21 key points in x, y, and z coordinates as a feature. As classifiers, we chose the support vector machine (SVM) and the artificial neural network (ANN). This research found that SVM using a polynomial kernel is the best among all of the methods we used as a classifier method for the 3D value of 21 key points from the hand skeleton. The accuracy and F1-score from SVM using a polynomial kernel were 86.26% accuracy and 82% F1-score, respectively, representing the best performance for each class of all the methods we used in this research.

DOI： 10.5057/isase.2022-c000026

CiNii Research

その他リンク： https://www.jstage.jst.go.jp/article/isase/ISASE2022/0/ISASE2022_1_34/_pdf

特集：「地域における AI 社会実装」特集「地域における AI 社会実装」にあたって

吉田香, 諏訪博彦, 清田陽司

人工知能 ( 一般社団法人人工知能学会 ) 37 ( 2 ) 170 - 171 2022年01月

Calibration Cost Reduction of Indoor Localization Using Bluetooth Low Energy Beacon 査読有り国際誌

As M., Shimizu H., Benaissa B., Yoshida K., Koppen M.

Journal of Advanced Computational Intelligence and Intelligent Informatics ( 富士技術出版株式会社 ) 26 ( 1 ) 97 - 106 2022年01月

記述言語：英語掲載種別：研究論文（学術雑誌）

Indoor localization based on Bluetooth low energy (BLE) beacons has been rapidly developed, and many approaches have been developed to achieve higher estimation accuracy. In these methods, the received signal strength (RSS) is the input. However, the measurement of indoor environments is affected easily; the signal may be reflected and attenuated by obstacles such as the human body, walls, and furniture, which creates a challenge for methods based on signal mapping. In this study, BLE signal characteristics are investigated in an indoor localization setting. An experiment is performed using one BLE beacon and multiple receivers installed at different wall and ceiling positions. The raw RSS is observed, and the relationship between the BLE beacon signal strength characteristics against the human body effect as well as the receiver's placement in the observation area are discussed. Signal mapping is performed, where the signal strength is measured from all receivers simultaneously. The position estimation accuracy is examined based on different data scenarios. The results show that the estimation position estimated by the BLE beacon based on extensive BLE beacon data does not affect the estimation accuracy.

DOI： 10.20965/jaciii.2022.p0097

Scopus

CiNii Article

CiNii Research

その他リンク： https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85124460770&origin=inward

A First Prototype of an Emotional Smart Speaker 査読有り国際誌

Enrique A. de la Cal, Alberto Gallucci, José Ramón Villar, Kaori Yoshida, Mario Koeppen

Advances in Intelligent Systems and Computing 1401 304 - 313 2021年09月

A Feasibility Study on Hand Gesture Recognition in Natural Conversation 査読有り

Silpani D.C., Suematsu K., Yoshida K.

2021 5th IEEE International Conference on Cybernetics, CYBCONF 2021 85 - 90 2021年06月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

This paper proposes to approach natural hand gestures that occur in natural conversations. Hand gesture recognition in Human-Robot Interaction is considered a preliminary study for the next step, based on the vision system of a humanoid robot. We experimented as a feasibility study on hand gestures recognition in natural conversation. The conversations between an experimental assistant (the first author) and two different subjects (both female) were recorded in the experiment. Each conversation includes two people, one of whom is the subject of the hand gesture detection that appears during the conversation. We manually captured the hand gestures that appear naturally during the session and analyzed their duration and frequency of occurrence from each video. As a result of conversations with two subjects, it was clear that hand gestures significantly impact people's conversations. We observed that hand gestures with the same word or similar meaning appeared several times with the same intention, such as pointing at something and emphasizing a sentence or word. The topic of natural hand-gesture recognition by a robot will be a challenge. Cultural diversity makes the scope of natural hand-gesture broad, but this can be considered a topic in developing the knowledge of human-robot interaction in the future.

DOI： 10.1109/CYBCONF51991.2021.9464141

Scopus

その他リンク： https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85113788192&origin=inward

より良い未来のための社会実装

吉田香

人工知能 ( 一般社団法人人工知能学会 ) 36 ( 3 ) 335 - 335 2021年01月

Simple Meta-optimization of the Feature MFCC for Public Emotional Datasets Classification 査読有り国際誌

de la Cal E., Gallucci A., Villar J.R., Yoshida K., Koeppen M.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 12886 LNAI 659 - 670 2021年01月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

A Speech Emotion Recognition (SER) system can be defined as a collection of methodologies that process and classify speech signals to detect emotions embedded in them [2]. Among the most critical issues to consider in an SER system are: i) definition of the kind of emotions to classify, ii) look for suitable datasets, iii) selection of the proper input features and iv) optimisation of the convenient features. This work will consider four of the well-known dataset in the literature: EmoDB, TESS, SAVEE and RAVDSS. Thus, this study focuses on designing a low-power SER algorithm based on combining one prosodic feature with six spectral features to capture the rhythm and frequency. The proposal compares eleven low-power Classical classification Machine Learning techniques (CML), where the main novelty is optimising the two main parameters of the MFCC spectral feature through the meta-heuristic technique SA: the n_mfcc and the hop_length. The resulting algorithm could be deployed on low-cost embedded systems with limited computational power like a smart speaker. In addition, the proposed SER algorithm will be validated for four well-known SER datasets. The obtained models for the eleven CML techniques with the optimised MFCC features outperforms clearly (more than a 10%) the baseline models obtained with the not-optimised MFCC for the studied datasets.

DOI： 10.1007/978-3-030-86271-8_55

Scopus

その他リンク： https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85115856860&origin=inward

Smart watering system based on framework of low-bandwidth distributed applications (LBDA) in cloud computing 査読有り

Sirimorok N., As M., Yoshida K., Köppen M.

Advances in Intelligent Systems and Computing 1263 AISC 447 - 459 2021年01月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

The estimation of soil moisture content is required for agriculture, mainly to build the irrigation scheduling model. In this study, we present a smart watering system to deal with various factors derived from the stochastic information in the agricultural operational, i.e., air temperature, air humidity, soil moisture, soil temperature, and light intensity. The methodology consists of exploiting the Internet of Things (IoT) using Low-Bandwidth Distributed Applications (LBDA) in cloud computing to integrate the real data sets collected by the several sensor technologies. We conducted experiments for the watering system used two types of soil and different plant. Here, the Long Short Term Memory Networks (LSTMs) approach in deep learning techniques used to build smart decisions concerning watering requirements and deal with heterogeneous information coming from agricultural environments. Results show that our models can effectively improve the prediction accuracy for the watering system over various soil and plants.

DOI： 10.1007/978-3-030-57796-4_43

Scopus

その他リンク： https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85090100059&origin=inward

Hand Position Tracking Correction of Leap Motion Controller Attached to the Virtual Reality Headset 査読有り

BELANOVÁ Dorota, YOSHIDA Kaori

International Journal of Biomedical Soft Computing and Human Sciences: the official journal of the Biomedical Fuzzy Systems Association ( バイオメディカル・ファジィ・システム学会 ) 25 ( 1 ) 29 - 37 2020年01月

記述言語：英語掲載種別：研究論文（学術雑誌）

Considering the increasing number of patients with disabilities, especially of upper extremity, we decided to develop hand rehabilitation virtual reality system for post-stroke patients using leap motion controller. However, as the device has not met the required accuracy of hand position tracking, we created a real-time low-computational cost correction algorithm lessening the problem. This paper outlines the challenges of hand position tracking accuracy identifying the parts contributing to the overall error, proposes a method of correction suitable for each of the parts separately and brings the parts together into an algorithm maximizing the hand position correction. The algorithm was tested on twelve healthy participants in two series of four tasks. Results showed our algorithm improved the hand position accuracy considerably in all the cases.

DOI： 10.24466/ijbschs.25.1_29

CiNii Article

その他リンク： https://ci.nii.ac.jp/naid/130007998938

The Concept of Intelligent Space with a Robot 査読有り

BELANOVÁ Dorota, MACH Marián, SINČÁK Peter, YOSHIDA Kaori

International Symposium on Affective Science and Engineering 2019 ( 0 ) 1 - 4 2019年01月

記述言語：英語掲載種別：研究論文（学術雑誌）

Intelligent space is where people may easily interact with computers and robots, changing the environmental conditions based on users' needs to create more comfortable and satisfying surroundings. In our proposed system, we would integrate an intelligent space with a robot that would act as an active part of the environment. The system is illustrated in a few caregiver scenarios, showing the actions of a robot. The skills of a robot are explained, presenting the advantages and contributions of the system.

DOI： 10.5057/isase.2019-C000024

Kyutacar

CiNii Article

その他リンク： https://ci.nii.ac.jp/naid/130007656892

An Efficient Replay Method to Prevent SURF-Based Face Detection 査読有り

Dadkhah S., Koppen M., Sadeghi S., Yoshida K.

Proceedings - 2018 5th Asia-Pacific World Congress on Computer Science and Engineering, APWC on CSE 2018 18 - 25 2018年12月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

© 2018 IEEE. During the past couple of years, a considerable number of digital images are gathered by search engines, or uploaded by users in different social websites. These images could contain a variety of variables such as different faces, scenes, and unusual objects. The advancement of digital face recognition algorithms is sensational, recognition algorithms used by some of the social websites are even stronger than most secret service establishments. However, there is always a concern about how to protect the user's privacy when they do not want to be recognized automatically by these services. In this research, a SURF-based face recognition algorithm along with a featurebased attack to mislead this type of scheme is proposed. The recognition algorithm use different machine learning technique along with second layer descriptor counting function which makes it more powerful. However the primary focus of this research is to provide a method which can mislead this type of recognition systems with a smallest possible degradation to the image representation. The experimental results show that the proposed plan is successful to fool the SURF algorithm and its recognition system by 70%.

DOI： 10.1109/APWConCSE.2018.00012

Scopus

その他リンク： https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85074295713&origin=inward

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