AI Image Recognition Counting System: Automation of Counting Tasks - Case Study Introduction
Automating counting tasks using AI and image processing technology offers many benefits, such as improved accuracy, reduced work time, and cost savings.
Here is an example of inspecting the number of transparent zip bags. "Deep Counter" is an AI software that uses Deep Learning technology to achieve high-precision counting of unspecified items and objects placed in various orientations, which was difficult to accomplish with traditional rule-based image recognition technology. It counts quickly and accurately using Rist's unique AI algorithm, contributing to the reduction of manual counting tasks done by "visual inspection" on-site. 1. Improved accuracy: Prevents counting errors and oversights from manual work. 2. Time savings: Speeds up the process with cameras, improving work efficiency. 3. Alleviation of labor shortages: Reduces workload and addresses labor shortages. 4. Cost reduction: Cuts labor costs, reduces losses due to errors, and minimizes losses. 5. Data utilization: Enables real-time recording and monitoring, and can be used for data analysis.
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