Nobuyoshi Yabuki

Professor

Osaka Daigaku

Japan

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Professor Nobuyoshi Yabuki is a faculty member at Osaka Daigaku in Japan. His research areas encompass urban vegetation analysis through deep learning, construction site motion recognition, and innovations in mixed reality applications for architecture and education. His recent articles reflect a strong focus on integrating technology within environmental and infrastructural studies.

Nobuyoshi Yabuki

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Articles (15)

Multi-temporal analysis of urban vegetation using deep learning and 3D reconstruction

Earthwork Traceability Management System Using Compaction History and Dump Truck Sensing Data

A Mixed Reality Design System for Interior Renovation: Inpainting with 360-Degree Live Streaming and Generative Adversarial Networks after Removal

A Study on Differences in Educational Method to Periodic Inspection Work of Nuclear Power Plants

Motion Recognition Method for Construction Workers Using Selective Depth Inspection and Optimal Inertial Measurement Unit Sensors

Integrating GIS, deep learning, and environmental sensors for multicriteria evaluation of urban street walkability

STUDY ON UTILIZATION OF POINT CLOUD DATA FOR PILE CENTER POSITION MEASUREMENT IN PILE CONSTRUCTION,杭工事における杭芯計測への点群データの活用に関する研究

Scene Understanding for Dimensional Compliance Checks in Mixed-Reality

Measuring visual walkability perception using panoramic street view images, virtual reality, and deep learning

Automatic generation of synthetic datasets from a city digital twin for use in the instance segmentation of building facades

Diminished reality using semantic segmentation and generative adversarial network for landscape assessment: evaluation of image inpainting according to colour vision

Future landscape visualization using a city digital twin: integration of augmented reality and drones with implementation of 3D model-based occlusion handling

A SERVER-SIDE RENDERING METHOD FOR HANDLING LARGE-VOLUME 3D MODELS OF ENVIRONMENTAL DESIGN IN WEB-BASED AUGMENTED REALITY,大容量の環境設計3 次元モデルを Web AR で扱うためのサーバサイドレンダリング法

Exploring the association between street built environment and street vitality using deep learning methods

Development of a City-Scale Approach for Façade Color Measurement with Building Functional Classification Using Deep Learning and Street View Images

Collaborators (2)

Tomohiro Fukuda

ANQI HU

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