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ORCIDTsubasa Minematsu
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2020 – today
- 2024
[j8]Sukrit Leelaluk
, Cheng Tang, Tsubasa Minematsu, Yuta Taniguchi, Fumiya Okubo, Takayoshi Yamashita, Atsushi Shimada:
Attention-Based Artificial Neural Network for Student Performance Prediction Based on Learning Activities. IEEE Access 12: 100659-100675 (2024)- [j7]Yiding Li, Atsushi Shimada, Tsubasa Minematsu, Cheng Tang:
A framework of specialized knowledge distillation for Siamese tracker on challenging attributes. Mach. Vis. Appl. 35(4): 94 (2024) - [c28]Ivo Lodovico Molina, Valdemar Svábenský, Tsubasa Minematsu, Li Chen, Fumiya Okubo, Atsushi Shimada:
Comparison of Large Language Models for Generating Contextually Relevant Questions. EC-TEL (2) 2024: 137-143 - [c27]Yuma Miyazaki, Valdemar Svábenský, Yuta Taniguchi, Fumiya Okubo, Tsubasa Minematsu, Atsushi Shimada:
E2Vec: Feature Embedding with Temporal Information for Analyzing Student Actions in E-Book Systems. EDM 2024 - [c26]Cheng Tang, Li Chen, Gen Li, Tsubasa Minematsu, Fumiya Okubo, Yuta Taniguchi, Atsushi Shimada:
Visual Analytics of Learning Behavior Based on the Dendritic Neuron Model. KSEM (2) 2024: 192-203 - [i2]Yuma Miyazaki, Valdemar Svábenský, Yuta Taniguchi, Fumiya Okubo, Tsubasa Minematsu, Atsushi Shimada:
E2Vec: Feature Embedding with Temporal Information for Analyzing Student Actions in E-Book Systems. CoRR abs/2407.13053 (2024) - [i1]Ivo Lodovico Molina, Valdemar Svábenský, Tsubasa Minematsu, Li Chen, Fumiya Okubo, Atsushi Shimada:
Comparison of Large Language Models for Generating Contextually Relevant Questions. CoRR abs/2407.20578 (2024) - 2023
- [j6]Fumiya Okubo, Tetsuya Shiino, Tsubasa Minematsu, Yuta Taniguchi, Atsushi Shimada:
Adaptive Learning Support System Based on Automatic Recommendation of Personalized Review Materials. IEEE Trans. Learn. Technol. 16(1): 92-105 (2023) - [c25]Tsubasa Minematsu, Yuta Taniguchi, Atsushi Shimada:
Contrastive Learning for Reading Behavior Embedding in E-book System. AIED 2023: 426-437 - [c24]Sayaka Kogishi, Tsubasa Minematsu, Atsushi Shimada, Hiroaki Kawashima:
Predicting Student Scores Using Browsing Data and Content Information of Learning Materials. AIED (Posters/Late Breaking Results/...) 2023: 555-560 - [c23]Erwin D. López Z., Tsubasa Minematsu, Yuta Taniguchi, Fumiya Okubo, Atsushi Shimada:
LECTOR: An attention-based model to quantify e-book lecture slides and topics relationships. EDM 2023 - [c22]Yunyu Zhou, Tsubasa Minematsu, Atsushi Shimada:
Improvement of Image Segmentation Model for Handwritten Notebook Analytics. ICIP 2023: 1870-1874 - 2022
- [j5]Ahmed Gomaa, Tsubasa Minematsu, Moataz M. Abdelwahab, Mohammed Abo-Zahhad, Rin-Ichiro Taniguchi:
Faster CNN-based vehicle detection and counting strategy for fixed camera scenes. Multim. Tools Appl. 81(18): 25443-25471 (2022) - [c21]Taiki Hamada, Tsubasa Minematsu, Atsushi Shimada, Fumiya Okubo, Yuta Taniguchi:
Background Subtraction Network Module Ensemble for Background Scene Adaptation. AVSS 2022: 1-8 - [c20]Erwin D. López Z., Tsubasa Minematsu, Yuta Taniguchi, Fumiya Okubo, Atsushi Shimada:
Exploring the Use of Probabilistic Latent Representations to Encode the Students' Reading Characteristics. LAK (Data Challenge) 2022: 1-10 - [c19]Sukrit Leelaluk, Tsubasa Minematsu, Yuta Taniguchi, Fumiya Okubo, Atsushi Shimada:
Predicting Student Performance based on Lecture Materials Data using Neural Network Models. LAK (Data Challenge) 2022: 11-20 - [c18]Boyi Li, Tsubasa Minematsu, Yuta Taniguchi, Fumiya Okubo, Atsushi Shimada:
How Does Analysis of Handwritten Notes Provide Better Insights for Learning Behavior? LAK 2022: 549-555 - [c17]Sukrit Leelaluk, Tsubasa Minematsu, Yuta Taniguchi, Fumiya Okubo, Takayoshi Yamashita, Atsushi Shimada:
Scaled-Dot Product Attention for Early Detection of At-risk Students. TALE 2022: 316-322 - [c16]Kanu Shiga, Tsubasa Minematsu, Yuta Taniguchi, Fumiya Okubo, Atsushi Shimada, Rin-Ichiro Taniguchi:
Development and Evaluation of a Field Environment Digest System for Agricultural Education. WCCE 2022: 87-99 - [c15]Seiyu Okai, Tsubasa Minematsu, Fumiya Okubo, Yuta Taniguchi, Hideaki Uchiyama, Atsushi Shimada:
A System to Realize Time- and Location-Independent Teaching and Learning Among Learners Through Sharing Learning-Articles. WCCE 2022: 475-487 - 2021
- [c14]Yuta Taniguchi, Tsubasa Minematsu, Atsushi Shimada:
Composing Learning Environments with e-Textbook System (short paper). iTextbooks@AIED 2021: 35-39 - [c13]Ryusuke Murata, Tsubasa Minematsu, Atsushi Shimada:
Early Detection of At-risk Students based on Knowledge Distillation RNN Models. EDM 2021 - 2020
- [c12]Tsubasa Minematsu, Atsushi Shimada, Rin-Ichiro Taniguchi:
Visualization and Analysis for Supporting Teachers Using Clickstream Data and Eye Movement Data. HCI (23) 2020: 581-592 - [c11]Tsubasa Minematsu, Atsushi Shimada, Rin-Ichiro Taniguchi:
Rethinking Background And Foreground In Deep Neural Network-Based Background Subtraction. ICIP 2020: 3229-3233 - [c10]Takuro Owatari, Atsushi Shimada, Tsubasa Minematsu, Maiya Hori, Rin-Ichiro Taniguchi:
Real-Time Learning Analytics Dashboard for Students in Online Classes. TALE 2020: 523-529 - [c9]Tsubasa Minematsu, Manon Saguey, Atsushi Shimada, Rin-Ichiro Taniguchi:
Inactive Behavior Analytics In On-Site Lectures. TALE 2020: 708-713 - [c8]Sugino Nicolas Alejandro, Tsubasa Minematsu, Atsushi Shimada, Takashi Shibata, Rin-Ichiro Taniguchi, Eiji Kaneko, Hiroyoshi Miyano:
Semi-automatic Learning Framework Combining Object Detection and Background Subtraction. VISIGRAPP (5: VISAPP) 2020: 96-106
2010 – 2019
- 2019
- [j4]Ahmed Gomaa, Moataz M. Abdelwahab, Mohammed Abo-Zahhad, Tsubasa Minematsu, Rin-Ichiro Taniguchi:
Robust Vehicle Detection and Counting Algorithm Employing a Convolution Neural Network and Optical Flow. Sensors 19(20): 4588 (2019) - [c7]Tsubasa Minematsu, Atsushi Shimada, Rin-Ichiro Taniguchi:
Simple background subtraction constraint for weakly supervised background subtraction network. AVSS 2019: 1-8 - [c6]Atsushi Shimada, Tsubasa Minematsu, Masanori Yamada:
Advanced Tools for Digital Learning Management Systems in University Education. HCI (22) 2019: 419-429 - 2018
- [j3]Tsubasa Minematsu, Atsushi Shimada, Hideaki Uchiyama, Rin-Ichiro Taniguchi:
Analytics of Deep Neural Network-Based Background Subtraction. J. Imaging 4(6): 78 (2018) - [j2]Tsubasa Minematsu, Atsushi Shimada, Hideaki Uchiyama, Vincent Charvillat, Rin-Ichiro Taniguchi:
Reconstruction-Based Change Detection with Image Completion for a Free-Moving Camera. Sensors 18(4): 1232 (2018) - 2017
- [j1]Tsubasa Minematsu, Hideaki Uchiyama, Atsushi Shimada, Hajime Nagahara, Rin-Ichiro Taniguchi:
Adaptive background model registration for moving cameras. Pattern Recognit. Lett. 96: 86-95 (2017) - [c5]Tsubasa Minematsu, Atsushi Shimada, Rin-Ichiro Taniguchi:
Analytics of deep neural network in change detection. AVSS 2017: 1-6 - [c4]Tsubasa Minematsu, Atsushi Shimada, Hideaki Uchiyama, Rin-Ichiro Taniguchi:
Simple Combination of Appearance and Depth for Foreground Segmentation. ICIAP Workshops 2017: 266-277 - 2016
- [c3]Tsubasa Minematsu, Atsushi Shimada, Rin-Ichiro Taniguchi:
Background initialization based on bidirectional analysis and consensus voting. ICPR 2016: 126-131 - 2015
- [c2]Tsubasa Minematsu, Hideaki Uchiyama, Atsushi Shimada, Hajime Nagahara, Rin-Ichiro Taniguchi:
Evaluation of foreground detection methodology for a moving camera. FCV 2015: 1-4 - [c1]Tsubasa Minematsu, Hideaki Uchiyama, Atsushi Shimada, Hajime Nagahara, Rin-Ichiro Taniguchi:
Adaptive search of background models for object detection in images taken by moving cameras. ICIP 2015: 2626-2630
Coauthor Index
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