Qlean Dataset Launches 'Japanese Single-Family Home Exterior Image Dataset'

Visual Bank Co., Ltd. (Minato-ku, Tokyo, CEO: Masayuki Nagai), through its subsidiary amanaimages Inc., has launched the "Japanese Single-Family Home Exterior Image Dataset" under its AI training data solution, "Qlean Dataset." This dataset is optimized for improving object recognition accuracy using computer vision and for training image models aimed at understanding the specific spatial context of the Japanese residential environment.

This dataset consists of exterior images of single-family homes photographed in real-world environments across Japan, accompanied by metadata about the surrounding environment. It comprehensively covers the shapes, exterior wall textures, and roof structures of detached houses in various areas, including residential neighborhoods and suburbs throughout Japan. It is well-suited for building models that can identify specific architectural styles and for research and development in complex landscape analysis based on Japanese urban planning. By enabling deep learning of real-world visual features—such as road access conditions specific to residential areas, the positional relationships with adjacent structures, and variations in light and color due to time of day and weather—it facilitates advanced, context-aware image recognition.

This data is offered as part of the "AI Data Recipes," an original data lineup for AI development by Qlean Dataset. It is envisioned for use in practical AI development phases, ranging from the automation of real estate appraisals to the implementation of environmental recognition for autonomous driving and delivery robots in residential areas.

Visual Bank and amanaimages will continue to support the research and development of AI that accurately understands and analyzes Japan's residential environment by providing image and structural data that captures Japanese physical assets.