Zobrazeno 1 - 10
of 39
pro vyhledávání: '"Tsubasa Minematsu"'
Autor:
Sukrit Leelaluk, Cheng Tang, Tsubasa Minematsu, Yuta Taniguchi, Fumiya Okubo, Takayoshi Yamashita, Atsushi Shimada
Publikováno v:
IEEE Access, Vol 12, Pp 100659-100675 (2024)
Student performance prediction was deployed to predict learning performance to identify at-risk students and provide interventions for them. However, prediction models should also consider external factors along with learning activities, such as cour
Externí odkaz:
https://doaj.org/article/c132f9300ed643cc91eee7468b19ee16
Autor:
Ahmed Gomaa, Moataz M. Abdelwahab, Mohammed Abo-Zahhad, Tsubasa Minematsu, Rin-ichiro Taniguchi
Publikováno v:
Sensors, Vol 19, Iss 20, p 4588 (2019)
Automatic vehicle detection and counting are considered vital in improving traffic control and management. This work presents an effective algorithm for vehicle detection and counting in complex traffic scenes by combining both convolution neural net
Externí odkaz:
https://doaj.org/article/72158f43bd6f4dd99d66cc760a47dd38
Publikováno v:
Journal of Imaging, Vol 4, Iss 6, p 78 (2018)
Deep neural network-based (DNN-based) background subtraction has demonstrated excellent performance for moving object detection. The DNN-based background subtraction automatically learns the background features from training images and outperforms co
Externí odkaz:
https://doaj.org/article/5820b99b915a44dc8cdf645b1e876e9c
Autor:
Tsubasa Minematsu, Atsushi Shimada, Hideaki Uchiyama, Vincent Charvillat, Rin-ichiro Taniguchi
Publikováno v:
Sensors, Vol 18, Iss 4, p 1232 (2018)
Reconstruction-based change detection methods are robust for camera motion. The methods learn reconstruction of input images based on background images. Foreground regions are detected based on the magnitude of the difference between an input image a
Externí odkaz:
https://doaj.org/article/7b57d02083da429596377567ef842d66
Publikováno v:
IEEE Transactions on Learning Technologies. 16:92-105
Publikováno v:
Journal of Educational Computing Research. 61:639-670
This study helps improve the early prediction of student performance by RNN-FitNets, which applies knowledge distillation (KD) to the time series direction of the recurrent neural network (RNN) model. The RNN-FitNets replaces the teacher model in KD
The use of digital lecture slides in e-book platforms allows the analysis of students� reading behaviors. Previous works have made important contributions to this task, but they focused on students� interactions without considering the contents t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::247b846f76fcd6adedddb489e1abcef9
Autor:
Ahmed Gomaa, Tsubasa Minematsu, Moataz M. Abdelwahab, Mohammed Abo-Zahhad, Rin-ichiro Taniguchi
Publikováno v:
Multimedia Tools and Applications. 81:25443-25471
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
Publikováno v:
Sustainability; Volume 14; Issue 13; Pages: 8084
The COVID-19 pandemic has led to an increase in online classes, and programming classes are no exception. In such a learning environment, understanding every student’s programming process is mostly impractical for teachers, despite its significance
Publikováno v:
Journal of Educational Computing Research; Jun2023, Vol. 61 Issue 3, p639-670, 32p