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(2024.01.18)

Ligeng Chen, Zhenyang Zhu, Wangkang Huang, Kentaro Go, Xiaodiao Chen, Xiaoyang Mao, “Image recoloring for color vision deficiency compensation using Swin transformer,” Neural Computing and Applications, Springer, 2024-1. (IF:6.0(2022))

(2024.01.17)
GE Chao: FoV inspection using VR
JU Yixuan: Face editing using deep learning
Song Ziwei: Anomaly detection for onion using deep learning
ISHIKAWA Naohiko: Image editing for perceptual size restoration
TAMURA Shun: AR and deep learning for grape thinning support
YU Jun Wei: Color communication support for color vision deficiency compensation

Our research team is pleased to announce that our manuscript titled “3D Grape Bunch Model Reconstruction from 2D Images” has been accepted for publication in the journal Computers and Electronics in Agriculture.

This paper, authored by Yan San Woo, Zhuguang Li, Shun Tamura, Prawit Buayai, Hiromitsu Nishizaki, Koji Makino, Latifah Munirah Kamarudin, and Xiaoyang Mao, introduces a pioneering technology for reconstructing a 3D model of a grape bunch, with each berry uniquely identified, using 2D images captured in real grape field conditions. The development of this technology is set to reshape the grape cultivation landscape. By providing an accurate 3D model of grape bunches, it offers an innovative approach to automate berry counting and identification, enhancing the efficiency of the thinning process. This technology is particularly significant in the agriculture industry, where precision and automation are becoming increasingly vital.

This accomplishment underscores our commitment to advancing agricultural technology and contributing valuable insights to the industry. We extend our gratitude to our co-authors, contributors, and readers for their constant support.

The full paper can be accessed here.

Our research team is pleased to announce that our manuscript titled “End-to-End Lightweight Berry Number Prediction for Supporting Table Grape Cultivation,” has been accepted for publication in the journal Computers and Electronics in Agriculture.
This paper, authored by Yan San Woo, Prawit Buayai, Hiromitsu Nishizaki, Koji Makino, Latifah Munirah Kamarudin, and Xiaoyang Mao, introduces a novel lightweight system developed to automate the berry thinning process in table grape cultivation. The system incorporates advanced object detection techniques and is optimized for edge computing devices, which allows it to achieve high accuracy while maintaining a small computational footprint. This makes it particularly suitable for practical applications, even in locations with limited internet connectivity.
It is our hope that the results and insights provided in this paper will be a valuable contribution to the ongoing research and discussions in the field of agriculture technology. We extend our gratitude to our co-authors, contributors, and readers for their constant support.
The full paper can be accessed here.

We are excited to share that we recently hosted a group of brilliant students from the Institute of Science and Technology of the Royal Academy of Cambodia. This visit, which was a part of the Cultural and Educational Exchange Program (CEEP) 2023, took place on September 21st. The attendees were mainly fresh graduates, with a mix of computer science and food science specialties.

Our team had the privilege to introduce them to our state-of-the-art lab and showcase our pioneering grape cultivation support system. This innovative project, utilizing the latest AI and AR technologies, aims to transform the way grapes are grown, especially during critical stages such as berry thinning and harvesting.

The visit provided a great platform for us to delve into the technical aspects of our system and its impact on agricultural productivity. The students showed keen interest and their insightful questions added value to our ongoing development.

We extend our sincere gratitude to the CEEP 2023 delegation from the Royal Academy of Cambodia for their visit. Their active participation and engagement have greatly contributed to our venture in advancing the integration of technology and agriculture.

Please stay tuned for more updates on our website as we steadfastly work on refining our grape cultivation support system. We continue to strive for an era of precision and efficiency in agriculture, shaping a promising future for food production.

We eagerly anticipate future collaborations and cultural exchanges, and wish all the CEEP 2023 participants success in their forthcoming academic and professional endeavours. Thank you again, Royal Academy of Cambodia, for facilitating this enriching exchange of knowledge and perspectives.

We are thrilled to have recently welcomed a distinguished delegation from Ljubljana University to our lab, where we had the opportunity to demonstrate our groundbreaking grape cultivation support system. This innovative system, powered by the latest advancements in AI and AR technologies, is revolutionizing the way grapes are grown.

During their visit, which took place in the afternoon of September 5th, we were honored to showcase our table grape cultivation support system and its remarkable capabilities. With a specific focus on the berry thinning stage, we provided the delegation with a firsthand experience of the unprecedented efficiency that our system offers.

In collaboration with the esteemed Nishizaki lab, we combined forces to demonstrate the seamless integration of technology and agriculture, particularly in the harvesting stage of grape cultivation. This collaborative effort further highlighted the potential for increased productivity and enhanced techniques.

We extend our heartfelt gratitude to the delegation from Ljubljana University for their visit and their valuable contributions to our ongoing quest for innovation in grape cultivation. Their presence and engagement reaffirmed our commitment to advancing the field through cutting-edge technologies.

Stay tuned for more updates on our lab’s website as we continue to develop and refine our grape cultivation support system, paving the way for a new era of precision and efficiency in agriculture.

We are delighted to announce that our lab has had the privilege of hosting students from four prestigious universities as part of the “Asia Applied Artificial Intelligence (A3I): Real Problem Solving Driven Artificial Intelligence Education Program”. This program, adopted by the CAMPUS Asia Plus from the Ministry of Education, Culture, Sports, Science and Technology (MEXT) in Japan, aims to promote cultural exchanges among participating universities.

Co-organized by the University of Yamanashi (Japan), Hangzhou Dianzi University (China), Pukyong National University (South Korea), and University Malaysia Perlis (Malaysia), the A3I program is conducted in English as the common language, fostering collaboration and connecting these four countries.

During the program, we had the opportunity to introduce our lab and showcase our cutting-edge research in supporting table grape berry thinning and harvesting. The demonstration mainly focused on our system, which utilizes deep neural networks and augmented reality technologies to enhance the efficiency and accuracy of table grape berry thinning. Additionally, we demonstrated our table grape harvesting grading system, which plays a vital role in ensuring the quality and uniformity of the harvested grapes. Lastly, we showcased our robot system designed for table grape berry thinning, which highlights the potential for automation in the agricultural industry.

We were thrilled to share our research with the students and exchange insights and ideas throughout the program. It was a great opportunity to collaborate with bright minds from different cultural backgrounds and gain new perspectives on AI-driven problem-solving.

We extend our sincere appreciation to the A3I program, the participating universities, and the students for their enthusiastic engagement. Their presence and contributions have enriched our research environment and further strengthened our commitment to advancing the application of artificial intelligence in agriculture.

Stay tuned for more updates on our ongoing research and future collaborations. We look forward to continued fruitful partnerships in the field of applied artificial intelligence.

We’re pleased to inform you that our paper, “Supporting Table Grape Berry Thinning with Deep Neural Network and Augmented Reality Technologies,” has been published in Computers and Electronics in Agriculture.

Authored by Prawit Buayai, Kabin Yok-In, Daisuke Inoue, Hiromitsu Nishizaki, Koji Makino, and Xiaoyang Mao, our research delves into the application of deep neural network and augmented reality technologies to assist in table grape berry thinning.

Published on August 27, 2023, our work contributes to the ongoing evolution of agricultural technologies. We particularly highlight the utilization of deep neural networks and augmented reality, fostering advancements in agricultural practices.

For a comprehensive understanding of our research, you can access the paper via this link.

We are grateful to all the researchers and supporters involved in this project. Our commitment remains steady in exploring and sharing new technologies in agriculture.

We are excited to share that our research paper titled “AiRcupid: Supporting Cucumber Picking for Intellectual Disabilities using Artificial Intelligence and Augmented Reality” has been accepted into the esteemed 3rd Workshop on University Augmented Interaction (UNAI) and the highly regarded 2023 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct).

Authored by Daisuke Inoue, Kaishi Naito, Prawit Buayai, and Xiaoyang Mao, our research introduces an innovative solution that combines the power of artificial intelligence (AI) and augmented reality (AR) to support individuals with intellectual disabilities in cucumber picking.

ISMAR2023 conference website

We are thrilled to announce that our paper titled “BerryScope: AR Strawberry Picking Aid” has been accepted into the prestigious 2023 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct). Authored by Shun Tamura, Prawit Buayai, and Xiaoyang Mao, this research highlights our groundbreaking work in leveraging augmented reality technology to enhance strawberry harvesting.

Accepted on August 8, 2023, this achievement underscores our commitment to advancing the applications of augmented reality in the agricultural sector. Through the use of advanced computer vision techniques and augmented reality technologies, our team has developed an innovative solution to improve the efficiency and accuracy of strawberry picking.

ISMAR23 Conference URL

Shota Chiba, Zhenyang Zhu, Daisuke Inoue, Xiaoyang Mao, “Deep Learning and Augmented-Reality Glasses based Meat Cooking Support for Color Vision Disorder Compensation,” in the Proceedings of NICOGRAPH International 2023, Article L7, 2023-6. 【Detail】

Zhenyang Zhu*, Katsuhito Moritake*, Kenji Kashiwagi, Masahiro Toyoura, Kentaro Go, Issei Fujishiro, Xiaoyang Mao, “Metamorphopsia Insepction System based on Relevance Feedback”, International Conference on System, Man and Cybernetics, accepted 2023-6-1.
(*: co-first authors)

Homepage

Project Name: Smart Glasses for Grape Thinning
Date: May 19, 10:00 am – 3:00pm

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