#Japan #AI Solutions #Tokyo #Qlean Dataset #Visual Bank

Introduction

Visual Bank Inc., headquartered in Minato Ward, Tokyo, is making strides in AI data solutions through its subsidiary, Amana Images. Among its innovative offerings is the `Qlean Dataset`, a comprehensive AI training data solution tailored for research and commercial AI development. Recently, Visual Bank has broadened this dataset by introducing the `Japanese Station Exterior Image Dataset`, enhancing its unique lineup known as `AI Data Recipes`.

Overview of Qlean Dataset

The `Qlean Dataset` is designed to support both research and commercial applications. The addition of the Japanese Station Exterior Image Dataset includes a rich collection of images, reflecting the exterior architecture of various train stations across Japan. This dataset will significantly ease the burden of data collection and organization for AI developers and researchers, allowing them to concentrate on what matters most: innovation.

Dataset Details

• - Content: Images capturing the exterior views of train stations across Japan.
• - Format: JPEG.
• - Number of Images: 270.
• - Resolution: Images with a minimum width of 3,700 pixels.
• - Sample Details: For a closer look, users can access sample data here.

Potential Use Cases

The newly available dataset presents numerous applications across different fields:

Urban Landscape Analysis

AI developers can utilize this dataset to analyze various aspects of urban environments. It comprehensively covers architectural designs and structural variations in train stations. This data serves as an excellent training set for urban classification AI and geographical analysis models, aiding in automatic recognition and research on urban landscape analysis.

Station Recognition and Location Estimation AI

Images that feature station name signs and structural characteristics are invaluable for training models that estimate locations from images. Such technology can be applied in navigation systems and mobile apps, enhancing user experience in tourism and smart city development.

Architectural and Infrastructure Analysis

The dataset includes diverse architectural designs, materials, and structural variations relevant to train stations, making it an essential resource for AI research in architecture style classification and public infrastructure deterioration detection. These tools are vital for urban design, structural analysis, and infrastructure management applications.

Generative AI and Landscape Synthesis

The inclusion of high-resolution exterior images is particularly beneficial for generative AI models focused on landscape reconstruction and urban generation. Researchers working in creative domains, such as virtual cities and the metaverse, can leverage these images to create realistic environments.

Multi-Language Sign Recognition AI

The dataset’s incorporation of station signs can enhance optical character recognition (OCR) and text recognition systems, supporting research in areas like tourism information, translation, and visual assistance systems.

Characteristics of Qlean Dataset

• - Comprehensive Agreement: All data collected comes with consent for use, ensuring compliance with international privacy policies and allowing secure research or commercial utilization.
• - Fast and Efficient Data Acquisition: Utilizing the `AI Data Recipe`, users can obtain datasets efficiently, maximizing return on investment while minimizing initial expenses.
• - Tailored Data Solutions: If a specific dataset is not available in the `AI Data Recipe`, Visual Bank can customize and create datasets according to individual requirements.

For inquiries and further information about the Qlean Dataset, visit the contact page or access the service site here.

Academic Support Program

As part of its commitment to academia, Visual Bank is launching a program to provide datasets at no cost to universities, research institutions, and non-profit technical development teams. This initiative aims to address the challenge of obtaining high-quality, rights-cleared learning data. Qlean Dataset offers access to over 500,000 data points across more than 80 types, including images, audio, video, and text. Learn more about this initiative here.

About Visual Bank Inc.

Visual Bank is a forward-thinking startup dedicated to building and providing next-generation data infrastructures aimed at maximizing AI development capabilities. With a mission to "unleash the potential of all data," the company supports creative endeavors through tools like `THE PEN`, an AI-assisted tool for artists, alongside the development of the `Qlean Dataset`.

The CEO, Masayuki Nagai, leads the company's initiatives from their office located at 6F C-Cube Minami-Aoyama Building, 7-1-7 Minamiaoyama, 107-0062 Tokyo. For more information, visit Visual Bank's website here and Amana Images here.