Introduction:

Artificial Intelligence (AI) and Machine Learning (ML) have taken the front seat in Digital Transformation. This was possible only with the innovation in science and technology in the past few years.

An innumerable data set is needed, which facilitates machines to easily recognize objects through diverse annotation techniques. There may be variation owing to the use case requirements. Whether it’s the autonomous car, facial recognition, medical imaging, or other AI/ ML models, a set procedure of annotation and labeling is needed.

Taking into account the versatility of the projects, the collation of such wide and diverse datasets will be beyond the imagination of the companies. To be precise, it applies to companies involved in AI or ML development. Moreover, the budget and team involvement constraint does not have any say in such development processes.

Hence, outsourcing data annotation and labeling projects to a particular affiliate will aid a company to get the right data. They will be in accordance with the project requirements and budget constraints.

What is Image Annotation?

‘Image Annotation’ is the process of labeling images. It is a part of the machine learning model. Image Annotation aids the computer to understand the visuals on its own after the completion of the data set.

Image Annotation is usually executed in a computer-assisted model. The engineer is expected to come up with the label definition. They should also provide image-specific information to the computer.

Even after the engineer has labeled all the images in a data set, the computer will continue to recognize the predetermined features in the new images. The significant point here is that it includes the ones that the engineer has not labeled.

The activity of image annotation is part of the machine learning process that helps create a set of databases. It is helpful in myriad industries like e-commerce, logistics, agriculture, healthcare, security, and much more.

Here is why image annotation services are essential for today’s business:

Object Detection

Image annotation allows the computer to trace out the various objects in a machine-learning process. Whether your system is powered by artificial intelligence or machine learning, you need to train the system via image/video annotation to get a hang of various objects.

Object Classification

Image annotation does not refrain to object detection. You can also classify the various objects in various categories as part of this exercise subsequently.

Data Validation

The image annotation tool is essential for a business lately. This tool can create model validation training data. It enables computer vision to understand the next set of images on its own. Nonetheless, it is a critical feature to enable the computer to use AI.

Accuracy

Image annotation skyrockets the level of accuracy of computer vision in the project.

Things to consider while outsourcing Image Annotation

We take our vision for a ride. With computer vision, we’ve unraveled many futuristic technologies much sooner than we’d anticipated. Its applications include:

• Facial recognition: On top of unlocking your phone, this technology identifies faces, even when they are hidden within a crowd. Amazing, isn’t it? This has reinvented security standards. For instance, if you shake a fist at someone under knifepoint, facial recognition technology can nab you in under 24 hours.

• Autonomous Vehicles: Nothing says innovative like self-driving cars. But the future is much closer than you think. We can take into account the riderless vehicles making food deliveries on behalf of food banks during the pandemic.
• Robotics: When you consider the productivity of industrial robots, one robot with built-in computer vision is worth multiple blind robots. A sharp robot can easily transport items from one place to another while eschewing workers and other robots.

None of the above would be possible without a vital technique: ‘Image and Video Annotation’. In other words, for a machine to recognize its surroundings, it is mandatory to train it properly.

So, how do companies/corporate running short on time and money ensure that training datasets for computer vision AI are accurate?

The answer is simple and easy — they just outsource data annotation to the Professionals.

5 Rationales to Outsource Image & Video Annotation

1.Time Investment

There is no need to waste your time and money piling tens of thousands of images and videos at your employees’ feet. Without the right and professional expertise, the annotation will turn out to be a time-consuming and labor-intensive process.

Data annotation services have been designed exclusively for data annotation. You can leave it to the professionals to deliver the goods without slowing down the ongoing in-house projects, in particular. In addition, not compromising on the accuracy of your training datasets.

2. Top-notch quality Datasets

By feeding the system inaccurate training datasets, wrong lessons will be taught to AI. In order to avoid misaligned bounding boxes and confusion in the classifiers, you can go for outsourcing. Outsourcing image annotation to a team of professional annotators can be a well-acclaimed solution.

3. Internal BiasMitigation

Bias is terribly bad news in Machine Learning. When your results are systematically prejudiced, your end solution suffers vehemently. Therefore, ‘Mitigating Bias’ is one of the major advantages of video and image annotation outsourcing for AI.

4. Scalability

Regardless of the scope pertaining to your Machine Learning project, training your model certainly demands a high volume of accurate data. Large-scale data annotation takes training, time, and manpower resources that most companies simply can’t think of/ afford.

Instead, outsource your data-labeling tasks to a team of professional annotators who dish out high-quality results.

5. Trained Professionals

Annotation is phenomenally time-consuming and laborious if you don’t possess the apt training and experience. You can rely on the annotators as they are well-equipped to tackle high volumes of complex data.

Now, let us focus on the aspects of why data annotation outsourcing is the right choice for all AI and machine learning companies, in particular.

• High-Quality Data Sets
• Scalability with Right TAT
• Data Security & Confidentiality
• Timely Availability
• Rationalize In-House Biasing

Conclusion:

If you are in search of a cost-effective method, you should go for outsourcing. This paves the way to get the image annotation services of an expert team. In addition, you can also expect more agility in the processes.

To explore further, you can reach IG Solutions, the best image, and video annotation services, provider!!!