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How Businesses Use Image Annotation to Produce High-Quality Training Data

When a company is done with collecting raw data from various sources, the business needs to feed it to the machines so that they understand it and produce accurate output. But before businesses provide data input to the machines, they need to label the raw data. The business that collects visual images as their data needs to carry out image annotation. Through this process, annotators label the different figures in the image, like human figures, objects, etc., so that machines understand these labels and process them accordingly to generate high-quality results. But image annotation is not as easy a process as it seems, so if you want to know about the process in depth, continue reading.

Many of us have been fined or know someone who has been fined by the traffic department’s automated speed-tracking system. But what makes these speed-capturing devices so efficient? How are they able to judge the speed of a moving vehicle and trigger an alert in a fraction of a second? This is a major example of an AI-based application, and image annotation lies at the core of such computer vision models.

Implementing artificial intelligence in any form involves training the machine to understand an environment like a human does. That requires well-labeled datasets. Raw data needs to be labeled and processed so that machines can use it to learn and replicate human behavior. Image annotation is the labeling of visuals to help computers recognize similar items in different images. Once the AI module is trained on a few images, it becomes capable of doing it for thousands or even millions of images in any database.

This blog outlines the major applications of image annotation in the present-day business world. We’ll also discuss how you can outsource image annotation services to make this process easier for your business.

Applications of Image Annotation

High-quality image annotation has already proven its worth in the fields of surveillance, security, healthcare, agriculture, logistics, e-commerce, and many more. Here are a few examples of the same

Helps the finance industry

The majority of companies’ finance departments have yet to fully realize the benefits of image annotation, but this sector is already reaping several benefits. One example of this is using face detection for customer ID verification when withdrawing money from an ATM. It’s done using the pose-point technique of image annotation. In the pose-point method, image annotation helps in mapping facial features such as the mouth, eyes, hair, etc. It’s incredibly beneficial for reducing potential fraud.

Image Annotation in Retail

In retail, image annotation is often used to build AI-based recommendation engines. It helps refine the consumer’s journey. When they type in a query or perform an image search, the recommendation engine can return closely related results and help the consumer easily find the product they are looking for.

Image Annotation in the Manufacturing Industry

It helps in capturing inventory information for better warehouse management. Computers are trained (using image annotation) to identify which product is going to be out of stock. It even helps in recognizing defective or incomplete items (for example, missing chargers from mobile device packaging) during packaging work.

AI-Powered Healthcare

Artificial intelligence powers a big segment of the healthcare industry. From robots that assist in surgery to software that can quickly analyze reports, x-rays, and other such imagery to create diagnoses, Additionally, image annotation has also proved to be highly beneficial in medical research, like differentiating cancer cells from healthy ones.

How Can You Make Image Annotation Easy for Your Business?

The most common options to get image annotation done quickly, reliably, and cost-effectively are:

Outsourcing

You can delegate image annotation services to reputed third-party companies and pay on an hourly basis or a project basis. Such organizations have the resources and infrastructure to produce unrivaled data quality. Furthermore, the results are delivered quickly.

Crowdfunding

The cost-cutting is the greatest in this method, but the quality is the lowest of the four. That’s because when you do crowdfunding, you will find that image annotation is performed by almost anybody with very little quality control. This method is also the most time-consuming.

Freelancers

This is the second-most cost-effective option, and the data quality is superior to that of crowdfunding. However, the quality of the results is determined by the type of resource obtained. It requires less time and more money than crowdfunding. Efficiency and effectiveness are similar to those of an in-house department.

Hiring In-house employees

This method of image and video annotation provides the highest level of privacy and direct control over work and employees, but it is also the most expensive and exhausting. The quality of work improves after a long time, and efficiency and effectiveness may be better than freelancing.

Out of all four, the most preferred one remains outsourcing your business needs to expert image and video annotation services. The primary

The benefits of outsourcing your image annotation requirement to an agency are:

  • Highly cost-effective
  • Unmatched quality of annotated images
  • Reduces the workload on your internal team
  • Highly flexible in scalability
  • It eliminates the need for hiring and training and eliminates waiting time until the in-house team develops expertise.

Conclusion

Companies that need to carry out image annotation on a large scale should be very wary of poorly labeled datasets. Poor-quality data will impact the efficiency of the machine-learning models because the machine will not be able to fully recognize and process the data. Thus, brands need to provide AI models with high-quality labeled data.

To do so, companies have different options, like setting up in-house teams, hiring freelancers, or outsourcing image annotation services. Choose the one that suits your needs and fits your budget.

Written By

Hello, I am Jessica Campbell, working as a content strategist at Data4Amazon. Our teams have managed more than 1200+ Amazon stores, helping clients outperform competition across the marketplace along with relevant, accurate information, optimize their store, manage customer orders, track inventory and provide complete customer support. Data4Amazon’s rapid growth is a testament to the quality services and in-depth expertise that clients experience by partnering with them.

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