المؤلفون: Shimada, Atsushi, Mouri, Kousuke, Taniguchi, Yuta, Ogata, Hiroaki, Taniguchi, Rin-ichiro, Konomi, Shin'ichi

المصدر: International Educational Data Mining Society. 2019.

تمت مراجعته من قبل الزملاء: Y

Page Count: 10

الواصفات: Student Placement, Learning Activities, Learning Analytics, Cognitive Style, Simulation, Student Improvement, Course Descriptions, Lecture Method, Electronic Publishing, Books, Student Satisfaction, Scores, Student Behavior, Behavior Patterns, Cluster Grouping, Electronic Learning, Foreign Countries, College Students

مصطلحات جغرافية: Japan

مستخلص: In this paper, we focus on optimizing the assignment of students to courses. The target courses are conducted by different teachers using the same syllabus, course design, and lecture materials. More than 1,300 students are mechanically assigned to one of ten courses taught by different teachers. Therefore, mismatches often occur between students' learning behavior patterns and teachers' approach to teaching. As a result, students may be less satisfied, have a lower level of understanding of the material, and achieve less. To solve these problems, we propose a strategy to optimize the assignment of students to courses based on learning activity analytics. The contributions of this study are 1) clarifying the relationship between learning behavior pattern and teaching based on learning activity analytics using large-scale educational data, 2) optimizing the assignment of students to courses based on learning behavior pattern analytics, and 3) demonstrating the effectiveness of assignment optimization via simulation experiments. [For the full proceedings, see ED599096.]

Abstractor: As Provided

المؤلفون: Onoue, Akira, Shimada, Atsushi, Minematsu, Tsubasa, Taniguchi, Rin-Ichiro

المصدر: International Association for Development of the Information Society. 2019.

تمت مراجعته من قبل الزملاء: Y

Page Count: 8

الواصفات: Concept Mapping, Learning Processes, Cluster Grouping, Graphs, College Freshmen, Models

مستخلص: This study aimed to cluster learners based on the structures of the knowledge maps they created. Learners drew their own knowledge maps to reflect their learning activities. Our system collected individual knowledge maps from many learners and clustered them to generate an integrated version of the knowledge maps of each cluster. We applied the graph analysis method to extract important keywords from the knowledge map. The results of the analysis showed that the utilization of the knowledge map helped to improve lectures and grasp the learners' level of understanding. We conducted surveys asking course managers to evaluate the effectiveness of the integrated knowledge maps of learners included in the cluster and received both positive and negative responses. [For the complete proceedings, see ED608557.]

Abstractor: As Provided

المؤلفون: Nakayama, Keita, Shimada, Atsushi, Minematsu, Tsubasa, Taniguchi, Yuta, Taniguchi, Rin-Ichiro

المصدر: International Association for Development of the Information Society. 2019.

تمت مراجعته من قبل الزملاء: Y

Page Count: 8

الواصفات: Models, Information Dissemination, Internet, Educational Technology, Technology Uses in Education, Educational Improvement, Learning Analytics, Instructional Materials, Electronic Publishing, Lecture Method, Media Selection

مستخلص: Thanks to an increase in the amount of information on the Internet and the spread of ICT-supported educational environments, much attention has been paid to learning support based on "smart" recommendation technologies. In this study, we propose an education improvement model based on the recommender system using the human-in-the-loop design strategy. Our proposed model enhances not only learners via recommendation, but also teachers and the system itself through the interaction between teachers and the system. In this paper, we introduce the details of the proposed model and implementation strategy followed by a report of preliminary experimental results. [For the complete proceedings, see ED608557.]

Abstractor: As Provided

المؤلفون: Taniguchi, Rin-Ichiro, Arita, Daisaku, Shimada, Atsushi, Yamada, Masanori, Goda, Yoshiko, Yamamoto, Ryota, Okayasu, Takashi

المصدر: International Association for Development of the Information Society. 2019.

تمت مراجعته من قبل الزملاء: Y

Page Count: 7

الواصفات: Agricultural Production, Foreign Countries, Teaching Methods, Agricultural Education, Lecture Method, Experiential Learning, Knowledge Level, Instructional Design, Integrated Learning Systems, Educational Technology, Electronic Publishing

مصطلحات جغرافية: Japan

مستخلص: This paper presents an outline of our project, in which we develop an observation framework for integrating lecture and contextual learning in the field of crop cultivation. Specifically, we will use multi sensing of learners' activities in classrooms, and contextual learning in fieldwork, farm planting, and farming environments. The motivation for our project is twofold: First, crop cultivation provides a powerful illustration of educational technology. It requires both explicit knowledge (from lectures) and implicit knowledge (from contextual learning outside of class). Second, from a practical viewpoint, the number of Japanese farmers is shrinking due to low income and to aging population. Thus, in order to maintain crop yields, farming skills must be transferred efficiently to novice farm workers. Herein, the major features of our framework will be described. [For the complete proceedings, see ED608557.]

Abstractor: As Provided

المؤلفون: Onizuka, Hayato, Hayirci, Zehra, Thomas, Diego, Sugimoto, Akihiro, Uchiyama, Hideaki, Taniguchi, Rin-ichiro

مصطلحات موضوعية: Computer Science - Computer Vision and Pattern Recognition, Electrical Engineering and Systems Science - Image and Video Processing

الوصف: Recovering the 3D shape of a person from its 2D appearance is ill-posed due to ambiguities. Nevertheless, with the help of convolutional neural networks (CNN) and prior knowledge on the 3D human body, it is possible to overcome such ambiguities to recover detailed 3D shapes of human bodies from single images. Current solutions, however, fail to reconstruct all the details of a person wearing loose clothes. This is because of either (a) huge memory requirement that cannot be maintained even on modern GPUs or (b) the compact 3D representation that cannot encode all the details. In this paper, we propose the tetrahedral outer shell volumetric truncated signed distance function (TetraTSDF) model for the human body, and its corresponding part connection network (PCN) for 3D human body shape regression. Our proposed model is compact, dense, accurate, and yet well suited for CNN-based regression task. Our proposed PCN allows us to learn the distribution of the TSDF in the tetrahedral volume from a single image in an end-to-end manner. Results show that our proposed method allows to reconstruct detailed shapes of humans wearing loose clothes from single RGB images.

الوصول الحر: http://arxiv.org/abs/2004.10534Test

المؤلفون: Xu, Yichao, Nagahara, Hajime, Shimada, Atsushi, Taniguchi, Rin-ichiro

مصطلحات موضوعية: Computer Science - Computer Vision and Pattern Recognition

الوصف: The segmentation of transparent objects can be very useful in computer vision applications. However, because they borrow texture from their background and have a similar appearance to their surroundings, transparent objects are not handled well by regular image segmentation methods. We propose a method that overcomes these problems using the consistency and distortion properties of a light-field image. Graph-cut optimization is applied for the pixel labeling problem. The light-field linearity is used to estimate the likelihood of a pixel belonging to the transparent object or Lambertian background, and the occlusion detector is used to find the occlusion boundary. We acquire a light field dataset for the transparent object, and use this dataset to evaluate our method. The results demonstrate that the proposed method successfully segments transparent objects from the background.
Comment: 9 pages, 14 figures, 2 tables, ICCV 2015

الوصول الحر: http://arxiv.org/abs/1511.06853Test

المؤلفون: Potortì, Francesco, Park, Sangjoon, Crivello, Antonino, Palumbo, Filippo, GIROLAMI, MICHELE, Barsocchi, Paolo, Lee, Soyeon, Torres-Sospedra, Joaquín, Jimenez Ruiz, Antonio Ramon, Perez-Navarro, Antoni, Mendoza-Silva, Germán Martín, Seco, Fernando, ortiz, miguel, PERUL, Johan, Renaudin, Valerie, Kang, Hyunwoong, Park, Soyoung, Lee, Jae Hong, Park, Chan Gook, Ha, Jisu, Han, JaeSeung, Park, Changjun, Kim, Keunhye, Lee, Yonghyun, Gye, Seunghun, lee, keumryeol, Kim, Eunjee, Choi, Jeongsik, choi, Yang-Seok, Talwar, Shilpa, Cho, Seong Yun, Ben-Moshe, Boaz, Scherbakov, Alex, Antsfeld, Leonid, Sansano-Sansano, Emilio, Chidlovskii, Boris, Kronenwett, Nikolai, Prophet, Silvia, Landay, Yael, Marbel, Revital, Zheng, Lingxiang, Peng, Ao, Lin, Zhichao, Wu, Bang, Ma, Chengqi, Poslad, Stefan, Selviah, David, Wu, Wei, Ma, Zixiang, Zhang, Wenchao, Wei, Dongyan, Yuan, Hong, Jiang, Jun-Bang, Huang, Shao-Yung, Liu, Jing-Wen, Su, Kuan-Wu, Leu, Jenq-Shiou, Nishiguchi, Kazuki, BOUSSELHAM, Walid, Uchiyama, Hideaki, Thomas, Diego, Shimada, Atsushi, Taniguchi, Rin-ichiro, Cortés Puschel, Vicente, Lungenstrass, Tomás, Ashraf, Imran, Lee, Chanseok, Ali, Muhammad Usman, Im, Yeongjun, Kim, Gunzung, Eom, Jeongsook, Hur, Soojung, Park, Yongwan, Opiela, Miroslav, Moreira, Adriano, Nicolau, Maria João, Pendão, Cristiano, Silva, Ivo, Meneses, Filipe, Costa, António, Trogh, Jens, Plets, David, Chien, Ying-Ren, Chang, Tzu-Yu, Fang, Shih-Hau, Tsao, Yu

مصطلحات موضوعية: indoor localisation, indoor navigation, competition, benchmarking, smartphone-based positioning, foot-mounted pedestrian dead reckoning, Wi-Fi fingerprinting, magnetic field, camera-based positioning, inertial-based positioning, sensor fusion, Kalman filter, particle filter, stakeholders, atmospheric measurements, particle measurements, real-time systems, wireless fidelity, sensor systems

الوصف: IPIN 2019 Competition, sixth in a series of IPIN competitions, was held at the CNR Research Area of Pisa (IT), integrated into the program of the IPIN 2019 Conference. It included two on-site real-time Tracks and three off-site Tracks. The four Tracks presented in this paper were set in the same environment, made of two buildings close together for a total usable area of 1000 m 2 outdoors and and 6000 m 2 indoors over three floors, with a total path length exceeding 500 m. IPIN competitions, based on the EvAAL framework, have aimed at comparing the accuracy performance of personal positioning systems in fair and realistic conditions: past editions of the competition were carried in big conference settings, university campuses and a shopping mall. Positioning accuracy is computed while the person carrying the system under test walks at normal walking speed, uses lifts and goes up and down stairs or briefly stops at given points. Results presented here are a showcase of state-of-the-art systems tested side by side in real-world settings as part of the on-site real-time competition Tracks. Results for off-site Tracks allow a detailed and reproducible comparison of the most recent positioning and tracking algorithms in the same environment as the on-site Tracks.

وصف الملف: application/pdf

العلاقة: Development of human enhancement fire helmet and fire suppression support system; Basic Science Research Program; ICT Research and Development Program of MSIP/IITP (Development of Precise Positioning Technology for the Enhancement of Pedestrian Position/Spatial Cognition and Sports Competition Analysis); MICROCEBUS; REPNIN PLUS; TECHNOFUSION(III)CM; Development of wireless communication tracking-based location information system in disaster scene for fire-fighters and person who requested rescue; Strategic Priority Research Program; IEEE Access, Vol. 8 (2020); F. Potortì et al., "The IPIN 2019 Indoor Localisation Competition—Description and Results," in IEEE Access, vol. 8, pp. 206674-206718, 2020, doi:10.1109/ACCESS.2020.3037221.; http://hdl.handle.net/10234/200929Test

الإتاحة: https://doi.org/10.1109/ACCESS.2020.3037221Test
http://hdl.handle.net/10234/200929Test

المؤلفون: Gomaa, Ahmed, Minematsu, Tsubasa, Abdelwahab, Moataz M., Abo-Zahhad, Mohammed, Taniguchi, Rin-ichiro

المساهمون: The National Research Institute of Astronomy and Geophysics

المصدر: Multimedia Tools and Applications ; volume 81, issue 18, page 25443-25471 ; ISSN 1380-7501 1573-7721

مصطلحات موضوعية: Computer Networks and Communications, Hardware and Architecture, Media Technology, Software

الوصف: Automatic detection and counting of vehicles in a video is a challenging task and has become a key application area of traffic monitoring and management. In this paper, an efficient real-time approach for the detection and counting of moving vehicles is presented based on YOLOv2 and features point motion analysis. The work is based on synchronous vehicle features detection and tracking to achieve accurate counting results. The proposed strategy works in two phases; the first one is vehicle detection and the second is the counting of moving vehicles. Different convolutional neural networks including pixel by pixel classification networks and regression networks are investigated to improve the detection and counting decisions. For initial object detection, we have utilized state-of-the-art faster deep learning object detection algorithm YOLOv2 before refining them using K-means clustering and KLT tracker. Then an efficient approach is introduced using temporal information of the detection and tracking feature points between the framesets to assign each vehicle label with their corresponding trajectories and truly counted it. Experimental results on twelve challenging videos have shown that the proposed scheme generally outperforms state-of-the-art strategies. Moreover, the proposed approach using YOLOv2 increases the average time performance for the twelve tested sequences by 93.4% and 98.9% from 1.24 frames per second achieved using Faster Region-based Convolutional Neural Network (F R-CNN ) and 0.19 frames per second achieved using the background subtraction based CNN approach (BS-CNN ), respectively to 18.7 frames per second.

الإتاحة: https://doi.org/10.1007/s11042-022-12370-9Test

المؤلفون: Xu, Yichao, Maeno, Kazuki, Nagahara, Hajime, Taniguchi, Rin-ichiro

مصطلحات موضوعية: Computer Science - Computer Vision and Pattern Recognition

الوصف: The light field camera is useful for computer graphics and vision applications. Calibration is an essential step for these applications. After calibration, we can rectify the captured image by using the calibrated camera parameters. However, the large camera array calibration method, which assumes that all cameras are on the same plane, ignores the orientation and intrinsic parameters. The multi-camera calibration technique usually assumes that the working volume and viewpoints are fixed. In this paper, we describe a calibration algorithm suitable for a mobile camera array based light field acquisition system. The algorithm performs in Zhang's style by moving a checkerboard, and computes the initial parameters in closed form. Global optimization is then applied to refine all the parameters simultaneously. Our implementation is rather flexible in that users can assign the number of viewpoints and refinement of intrinsic parameters is optional. Experiments on both simulated data and real data acquired by a commercial product show that our method yields good results. Digital refocusing application shows the calibrated light field can well focus to the target object we desired.
Comment: 11th International Conference on Quality Control by Artificial Vision (QCAV2013)

الوصول الحر: http://arxiv.org/abs/1407.4206Test

المؤلفون: Potorti, Francesco, Park, Sangjoon, Crivello, Antonino, Palumbo, Filippo, Girolami, Michele, Barsocchi, Paolo, Lee, Soyeon, Torres-Sospedra, Joaquin, Ruiz, Antonio Ramon Jimenez, Perez-Navarro, Antoni, Mendoza-Silva, German Martin, Seco, Fernando, Ortiz, Miguel, Perul, Johan, Renaudin, Valerie, Kang, Hyunwoong, Park, Soyoung, Lee, Jae Hong, Park, Chan Gook, Ha, Jisu, Han, Jaeseung, Park, Changjun, Kim, Keunhye, Lee, Yonghyun, Gye, Seunghun, Lee, Keumryeol, Kim, Eunjee, Choi, Jeong-Sik, Choi, Yang-Seok, Talwar, Shilpa, Cho, Seong Yun, Ben-Moshe, Boaz, Scherbakov, Alex, Antsfeld, Leonid, Sansano-Sansano, Emilio, Chidlovskii, Boris, Kronenwett, Nikolai, Prophet, Silvia, Landay, Yael, Marbel, Revital, Zheng, Lingxiang, Peng, Ao, Lin, Zhichao, Wu, Bang, Ma, Chengqi, Poslad, Stefan, Selviah, David R., Wu, Wei, Ma, Zixiang, Zhang, Wenchao, Wei, Dongyan, Yuan, Hong, Jiang, Jun-Bang, Huang, Shao-Yung, Liu, Jing-Wen, Su, Kuan-Wu, Leu, Jenq-Shiou, Nishiguchi, Kazuki, Bousselham, Walid, Uchiyama, Hideaki, Thomas, Diego, Shimada, Atsushi, Taniguchi, Rin-Ichiro, Puschel, Vicente Cortes, Poulsen, Tomas Lungenstrass, Ashraf, Imran, Lee, Chanseok, Ali, Muhammad Usman, Im, Yeongjun, Kim, Gunzung, Eom, Jeongsook, Hur, Soojung, Park, Yongwan, Opiela, Miroslav, Moreira, Adriano, Nicolau, Maria Joao, Pendao, Cristiano, Silva, Ivo, Meneses, Filipe, Costa, Antonio, Trogh, Jens, Plets, David, Chien, Ying-Ren, Chang, Tzu-Yu, Fang, Shih-Hau, Tsao, Yu

المصدر: IEEE access, 8, 206674–206718 ; ISSN: 2169-3536

مصطلحات موضوعية: ddc:620, Engineering & allied operations, info:eu-repo/classification/ddc/620

الوصف: PIN 2019 Competition, sixth in a series of IPIN competitions, was held at the CNR Research Area of Pisa (IT), integrated into the program of the IPIN 2019 Conference. It included two on-site real-time Tracks and three off-site Tracks. The four Tracks presented in this paper were set in the same environment, made of two buildings close together for a total usable area of 1000 m 2 outdoors and and 6000 m 2 indoors over three floors, with a total path length exceeding 500 m. IPIN competitions, based on the EvAAL framework, have aimed at comparing the accuracy performance of personal positioning systems in fair and realistic conditions: past editions of the competition were carried in big conference settings, university campuses and a shopping mall. Positioning accuracy is computed while the person carrying the system under test walks at normal walking speed, uses lifts and goes up and down stairs or briefly stops at given points. Results presented here are a showcase of state-of-the-art systems tested side by side in real-world settings as part of the on-site real-time competition Tracks. Results for off-site Tracks allow a detailed and reproducible comparison of the most recent positioning and tracking algorithms in the same environment as the on-site Tracks.

وصف الملف: application/pdf

العلاقة: info:eu-repo/semantics/altIdentifier/wos/000594446900001; info:eu-repo/semantics/altIdentifier/issn/2169-3536; https://publikationen.bibliothek.kit.edu/1000130123Test; https://publikationen.bibliothek.kit.edu/1000130123/104023450Test; https://doi.org/10.5445/IR/1000130123Test

الإتاحة: https://doi.org/10.5445/IR/1000130123Test
https://doi.org/10.1109/ACCESS.2020.3037221Test
https://publikationen.bibliothek.kit.edu/1000130123Test
https://publikationen.bibliothek.kit.edu/1000130123/104023450Test