scholarly journals Congratulations ! JACIII Best Paper and Young Researcher Awards 2021

2021 ◽  
Vol 25 (6) ◽  
pp. 925-928
Author(s):  
Keyword(s):  
Review Paper ◽  
Learning Algorithm ◽  
Object Oriented ◽  
Young Researcher ◽  
Semantic Mapping ◽  
Paper Award ◽  
Editorial Boards ◽  
Award Winning ◽  
Deep Forest ◽  
Network Object

We are pleased to announce that the JACIII Awards of 2021 have been decided by the JACIII editorial boards. This year, the award winning papers were severely and fairly selected among 362 papers published in JACIII Vols. 22 (2018) to 24 (2020) and there was no entries that deserved the Best Review Paper award. The award ceremony was held online in order to prevent spreading of COVID-19. JACIII BEST PAPER AWARD 2021 Sotetsu Suzugamine, Takeru Aoki, Keiki Takadama, and Hiroyuki Sato Self-Structured Cortical Learning Algorithm by Dynamically Adjusting Columns and Cells JACIII Vol.24 No.2, pp. 185-198, 2020. JACIII YOUNG RESEARCHER AWARD 2021 JACIII YOUNG RESEARCHER AWARD 2021 Xiaobo Liu Jinxin Chi Emotion Recognition Based on Multi-Composition Deep Forest and Transferred Convolutional Neural Network Object-Oriented 3D Semantic Mapping Based on Instance Segmentation By Xiaobo Liu, Xu Yin, Min Wang, Yaoming Cai, and Guang Qi By Jinxin Chi, Hao Wu, and Guohui Tian JACIII Vol.23 No.5, pp. 883-890, 2019. JACIII Vol.23 No.4, pp. 695-704, 2019.

scholarly journals Congratulations ! JACIII Best Paper and Young Researcher Awards 2020

2020 ◽  
Vol 24 (6) ◽  
pp. 707-709
Author(s):  
Keyword(s):  
Inertial Measurement Unit ◽  
Review Paper ◽  
Young Researcher ◽  
Measurement Unit ◽  
Paper Award ◽  
Boltzmann Machine ◽  
Inertial Measurement ◽  
Editorial Boards ◽  
Award Winning ◽  
Swimming Style

We are pleased to announce that the JACIII Awards of 2020 have been decided by the JACIII editorial boards. This year, the award winning papers were severely and fairly selected among 405 papers published in JACIII Vols. 21 (2017) to 23 (2019) and there was no entries that deserved the Best Review Paper award. The award ceremony was held online in order to prevent spreading of COVID-19. JACIII BEST PAPER AWARD 2020 Hiroki Shibata, Hiroshi Ishikawa, and Yasufumi Takama Crystalizing Effect of Simulated Annealing on Boltzmann Machine JACIII Vol.23 No.3, pp. 474-484, 2019. JACIII YOUNG RESEARCHER AWARD 2020 Yuto Omae Swimming Style Classification Based on Ensemble Learning and Adaptive Feature Value by Using Inertial Measurement Unit By Yuto Omae, Yoshihisa Kon, Masahiro Kobayashi, Kazuki Sakai, Akira Shionoya, Hirotaka Takahashi, Takuma Akiduki, Kazufumi Nakai, Nobuo Ezaki, Yoshihisa Sakurai, and Chikara Miyaji JACIII Vol.21 No.4, pp. 616-631, 2017. JACIII YOUNG RESEARCHER AWARD 2020 Caili Zhang Approach to Clustering with Variance-Based XCS By Caili Zhang, Takato Tatsumi, Masaya Nakata, and Keiki Takadama JACIII Vol.21 No.5, pp. 885-894, 2017.

Congratulations! JACIII Best Paper, Young Researcher, & Best Review Paper Awards 2019

2019 ◽  
Vol 23 (6) ◽  
pp. 967-969
Author(s):  
Keyword(s):  
Anomaly Detection ◽  
Rough Set ◽  
User Modeling ◽  
Review Paper ◽  
Young Researcher ◽  
Paper Award ◽  
Long Tail ◽  
Award Winning ◽  
Crowd Anomaly Detection

We are pleased to announce that the JACIII Awards of 2019 have been decided by the JACIII Editorial Board. This year, the award winning papers were severely and fairly selected among 399 papers published in JACIII Vols. 20 (2016) to 22 (2018). The awarding achievements of 2019 are as follows:   JACIII BEST PAPER AWARD 2019 Title: Analyzing Potential of Personal Values-Based User Modeling for Long Tail Item Recommendation Authors: Yasufumi Takama, Yu-Sheng Chen, Ryori Misawa, and Hiroshi Ishikawa <a href="https://www.fujipress.jp/jaciii/jc/jacii002200040506/" rel="noopener noreferrer" target="_blank">J. Adv. Comput. Intell. Intell. Inform., Vol.22 No.4, pp. 506-513, July 2018</a>   JACIII YOUNG RESEARCHER AWARD 2019 Title: Characteristics of Rough Set C-Means Clustering Authors: Seiki Ubukata, Keisuke Umado, Akira Notsu, and Katsuhiro Honda <a href="https://www.fujipress.jp/jaciii/jc/jacii002200040551/" rel="noopener noreferrer" target="_blank">J. Adv. Comput. Intell. Intell. Inform., Vol.22 No.4, pp. 551-564, July 2018</a>   JACIII BEST REVIEW PAPER AWARD 2019 Title: A Survey of Video-Based Crowd Anomaly Detection in Dense Scenes Authors: Junjie Ma, Yaping Dai, and Kaoru Hirota <a href="https://www.fujipress.jp//jaciii/jc/jacii002100020235/" rel="noopener noreferrer" target="_blank">J. Adv. Comput. Intell. Intell. Inform., Vol.21 No.2, pp. 235-246, March 2017</a>

scholarly journals Object-Oriented 3D Semantic Mapping Based on Instance Segmentation

2019 ◽  
Vol 23 (4) ◽  
pp. 695-704 ◽  
Author(s):  
Jinxin Chi ◽  
◽  
Hao Wu ◽  
Guohui Tian
Keyword(s):  
Object Recognition ◽  
Object Oriented ◽  
Mapping Method ◽  
Service Robots ◽  
Semantic Mapping ◽  
Continuous Image ◽  
Cloud Models ◽  
Localization And Mapping ◽  
Slam Algorithm ◽  
Instance Segmentation

Service robots gain both geometric and semantic information about the environment with the help of semantic mapping, providing more intelligent services. However, a majority of studies for semantic mapping thus far require priori knowledge 3D object models or maps with a few object categories that neglect separate individual objects. In view of these problems, an object-oriented 3D semantic mapping method is proposed by combining state-of-the-art deep-learning-based instance segmentation and a visual simultaneous localization and mapping (SLAM) algorithm, which helps robots not only gain navigation-oriented geometric information about the surrounding environment, but also obtain individually-oriented attribute and location information about the objects. Meanwhile, an object recognition and target association algorithm applied to continuous image frames is proposed by combining visual SLAM, which uses visual consistency between image frames to promote the result of object matching and recognition over continuous image frames, and improve the object recognition accuracy. Finally, a 3D semantic mapping system is implemented based on Mask R-CNN and ORB-SLAM2 frameworks. A simulation experiment is carried out on the ICL-NUIM dataset and the experimental results show that the system can generally recognize all the types of objects in the scene and generate fine point cloud models of these objects, which verifies the effectiveness of our algorithm.

Online Object-Oriented Semantic Mapping in Triger Classification Environment

2021 ◽  
pp. 304-313
Author(s):  
Wanlei Li ◽  
Yujing Chen ◽  
Haixiang Zhou ◽  
Minghui Hua ◽  
Yunjiang Lou
Keyword(s):  
Object Oriented ◽  
Semantic Mapping

scholarly journals Efficient Object-Oriented Semantic Mapping With Object Detector

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 3206-3213 ◽  
Author(s):  
Yoshikatsu Nakajima ◽  
Hideo Saito
Keyword(s):  
Object Oriented ◽  
Semantic Mapping
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