Proven Projects
Every project is proven through real-world validation. See results built on research-grade rigor.
The research foundation our founders built at university
粒羅 Tsubura — AI grape berry counting from your phone
An AI app born from University of Yamanashi research and used in the field.
Challenge
Konjac tubers have irregular shapes with frequent occlusion, making size and weight estimation inaccurate with conventional methods.
Solution
Developed a size and weight estimation method that handles occlusion, working even for partially hidden tubers.
Impact
Estimates size and weight reliably even for overlapping tubers, including hidden parts.
Challenge
Onion sorting relies on manual labor, with anomalies affecting quality and yield. Conventional image recognition lacked accuracy in real-world conditions.
Solution
Developed a feature-adaptive anomaly detection method, validated in both lab and real-world operational environments.
Impact
Delivers anomaly detection that works not only in the lab but on real sorting lines.
Challenge
Grape grading relies on expert visual assessment, leading to inconsistent standards and labor shortages.
Solution
Developed a deep learning grading system fusing multi-view imaging with IoT sensor data.
Impact
Fuses multi-view imaging and IoT sensing for stable grading without relying on manual labor.
Challenge
Grape berry thinning relies on skilled farmers' experience and intuition, making it difficult for newcomers and unskilled workers to learn.
Solution
Developed a system combining deep learning berry detection with AR glasses to display real-time thinning guidance.
Impact
Helps unskilled workers thin berries at a quality approaching that of experts.
Challenge
Grape berry thinning is highly manual labor, with severe workforce shortages and physical burden demanding automation.
Solution
Developed an automated thinning system combining berry detection AI with a robotic arm, validated in both indoor and field environments.
Impact
Demonstrated automated berry thinning in the field using berry-detection AI and a robotic arm.