Faculty Profiles - YOSHIDA Kaori

Papers - YOSHIDA Kaori

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A First Prototype of an Emotional Smart Speaker Reviewed International journal

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

Advances in Intelligent Systems and Computing 1401 304 - 313 2021.09

A Feasibility Study on Hand Gesture Recognition in Natural Conversation Reviewed

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

2021 5th IEEE International Conference on Cybernetics, CYBCONF 2021 85 - 90 2021.06

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 2021.01

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

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

Advances in Intelligent Systems and Computing 1263 AISC 447 - 459 2021.01

Language：English Publishing type：Research paper (international conference proceedings)

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

Other Link： https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85090100059&origin=inward

Simple Meta-optimization of the Feature MFCC for Public Emotional Datasets Classification Reviewed International journal

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 2021.01

Hand Position Tracking Correction of Leap Motion Controller Attached to the Virtual Reality Headset Reviewed

BELANOVÁ Dorota, YOSHIDA Kaori

International Journal of Biomedical Soft Computing and Human Sciences: the official journal of the Biomedical Fuzzy Systems Association 25 ( 1 ) 29 - 37 2020.01

The Concept of Intelligent Space with a Robot Reviewed

International Symposium on Affective Science and Engineering 2019 ( 0 ) 1 - 4 2019.01

Tensor self-organizing map for kansei analysis Reviewed

796 - 801 2018.12

An Efficient Replay Method to Prevent SURF-Based Face Detection Reviewed

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 2018.12

Language：English Publishing type：Research paper (international conference proceedings)

© 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

Other Link： https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85074295713&origin=inward

Updatable indoor localization based on BLE signal fingerprint Reviewed

2018.11

上半身動作を用いたロボットの回避方向意図の伝達 Reviewed

石川友紀也, 末松圭史, 大坪正和, 吉田香

日本知能情報ファジィ学会論文誌 30 ( 5 ) 709 - 716 2018.10

Path planning on robot based on D∗ lite algorithm Reviewed

Belanova D., Mach M., Sinčák P., Yoshida K.

DISA 2018 - IEEE World Symposium on Digital Intelligence for Systems and Machines, Proceedings 125 - 130 2018.10

An efficient ward-based copy-move forgery detection method for digital image forensic Reviewed

2017-December 1 - 6 2018.07

Phone Application for Indoor Localization Based on Ble Signal Fingerprint Reviewed

Benaissa B., Hendrichovsky F., Yishida K., Köppen M., Sinčák P.

2018 9th IFIP International Conference on New Technologies, Mobility and Security, NTMS 2018 - Proceedings 2018-January 1 - 5 2018.03

Language：English Publishing type：Research paper (international conference proceedings)

© 2018 IEEE. Indoor position of devices and persons is a very valuable information for context-aware devices and human activity recognition. The need of such information grows bigger by the advancement of IoT technologies. In this paper, we discuss existing indoor positioning approaches and their applications, give specific interest to the signal strength fingerprint approaches, to which belongs the presented paper. Bluetooth Low Energy Beacons are used as the source of the signal, and the Radial Basis Functions method is employed to create a model that relates to signal strength and position. The proposed approach allows the possibility of making all the computation on a smartphone application, namely, offline data collection and model computation, and online position estimation. Besides, it allows updating the model later.

DOI： 10.1109/NTMS.2018.8328729

Scopus

Other Link： https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85047863726&origin=inward

Bad Ai: Investigating the Effect of Half-Toning Techniques on Unwanted Face Detection Systems Reviewed

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

2018 9th IFIP International Conference on New Technologies, Mobility and Security, NTMS 2018 - Proceedings 2018-January 1 - 5 2018.03

BAD AI - Investigating the Effect of Half-Toning Techniques on Unwanted Face Detection Systems Reviewed

Sajjad Dadkhah and Mario Koeppen, Somayeh Sadeghi, Kaori Yoshida

the 9th IFIP International Conference on New Technologies, Mobility & Security 2018.02

Phone application for indoor localization based on BLE signal mapping Reviewed

Filip Hendrichovsky, Brahim Benaissa, Peter Sinčák, Kaori Yoshida

MobiCASE Student Workshop (MCSW2018) in conjunction with the 9th International Conference on Mobile Computing, Applications and Services (MobiCASE 2018) 2018.02

Challenges and Future Prospectives on User Modeling Reviewed

YOSHIDA Kaori

Journal of Japan Society for Fuzzy Theory and Intelligent Informatics ( Japan Society for Fuzzy Theory and Intelligent Informatics ) 30 ( 4 ) 219 - 221 2018.01

Interactive Evolutionary Computation of Color Palette Design Enhanced by Impression Words Reviewed

2017.03

CoWoOZ - A cloud-based teleoperation platform for social robotics Reviewed

49 - 54 2017.03

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Papers - YOSHIDA Kaori