Significantly reduced the selection time! We were able to greatly decrease the number of image points to be checked.
We would like to introduce a case where AI was implemented to extract suitable images that meet the criteria for publication in the media from a large number of images taken during sports events. In the case of our client, they traditionally took a large number of photos during sports events and manually extracted suitable images that met criteria such as "full body is visible" and "sports equipment is included." However, this selection process was time-consuming, and there was a demand for quicker extraction. To solve this issue, we created a system where AI extracts images that meet the criteria from thousands of target images, significantly reducing the number of images that need to be reviewed. For inquiries about the implementation of AI for the efficiency and automation of image and video-related tasks, please feel free to consult with Araya. [Effects After AI Implementation] ■ Significant reduction in selection time ■ Almost no time required for extraction *For more details, please refer to the PDF document or feel free to contact us.
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[Points of Consideration in AI Development] ■Combination of Extraction Conditions ■Selection of Suitable Algorithms *For more details, please refer to the PDF document or feel free to contact us.*
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【Purpose】 ■For those considering the introduction of AI to improve the efficiency of tasks related to images and videos - If you are checking a large number of images and videos manually - If there are many conditions to be extracted, etc. *For more details, please refer to the PDF document or feel free to contact us.
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Our company utilizes machine learning algorithms, particularly deep learning, to provide a wide range of services that can meet the diverse needs of our customers. Additionally, we are conducting research and development with an eye toward a future where robots possess "artificial consciousness" and begin to engage in advanced interactions with humans.
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