You must have seen it in Hollywood war movies, where a military drone is automatically identifying terrorists and executing them. Or, even for a more realistic day-to-day example, you may have unknowingly missed a red light, and you thought nobody noticed it. However, you received a dollar bill for the traffic violation at your address. If you are still pondering some supernatural force is messing up with you, read this blog to know who is exactly behind these actions.
To encompass the answer, in brief, it is – Image Annotation.
Image annotation is a process of labeling datasets to teach the computer vision models to detect the subject. Today, security cameras are everywhere and connected with AI & ML models. So anything passes in front of the camera, the AI & ML algorithm tries to find a match from the repository of accurately tagged data and identifies. If you thought nobody had seen you at the crossing, the security camera captured your face and car’s number plate. It matched with its massive repository in seconds, found your identity, notified the cops with details, and you were busted.
Let’s start with a statistic. The market for AI and machine learning data preparation is reaching $1.2 billion by 2023. (Source)
As the data suggests, the need for the image annotation process is growing day by day, and companies across industries look to prepare more data to train the AI & ML models for accurate prediction. Let’s find out how businesses across industries are benefiting from image annotation.
Image annotation empowers deep learning models to improve the accuracy of diagnosis and enhance the quality of treatment. Having precisely annotated data in the repository, the computer vision models can identify the images from CT, MRI, X-ray scans, etc. For example, it can interpret the patterns and pinpoint tumors, cancers, hairline fractures, abscesses, etc. Besides, it helps to eliminate costs on expensive scanner slots and reduce patient wait times.
Image annotation is extremely useful for the security and surveillance industry. Train the computer vision models to analyze human behavior, identify faces from the crowd to prevent serious crimes. Use 2D or 3D bounding boxes to mark and track the intruder throughout, even if they try to hide in the group. Additionally, you can train them to estimate the number of people, identify demographics, among others, etc. Use image annotation in strategic infrastructures, military base camps, radar centers, prisons, public security and safety and, government and private sectors. However, it is also effective in guarding industrial complexes, Banks, ATMs, Airports, Railway stations, shopping malls, etc.
Image annotation enhances the eCommerce customer experience. Annotators label specific captions and keywords to the product as it becomes easier for the website visitor to find what they are looking for. The image annotation process ensures that products are carrying correct information and categorized correctly for a better search relevance for product recommendations. Besides, Image annotation boosts visual search. For instance, you have an image of a particular designed item, but you forgot the product details so that you can drag the image on the website search bar. The deep learning algorithms will go through the repository and will take out the best match for you. Image annotation helps the user select the right product and saves time to experience an excellent shopping experience.
Self-driving cars are not new today. With the growing demand and rise in investment by customers, companies like Tesla, Uber, etc., are more committed to enhancing their technology for self-driving cars and autonomous taxis leveraging computer vision. Image annotation empowers automobile manufacturers to develop intelligent applications for connected and autonomous vehicles and self-driving cars. Besides, government sectors are also boosting digitization to create centralized and seamless traffic control. Hence, it is driving the image annotation & data labeling initiatives in the transport industry globally.
The introduction of image annotation has transformed the farming sector. From plants to crops, fruits, and even the soil are annotated for machines to recognize and take actions accordingly. It can also identify insects, unwanted crops, weeds, wildflowers, etc, and make the surface clean for the actual crop to grow. For precise detection of everything, accurate image annotation is required. Here, bounding boxes are a valuable technique for robots or drones to identify. Image annotation is also crucial in detecting soil health and field conditions. It can be used for geo sensing to determine the soil health condition and allow businesses to make the correct decision for harvesting or farming.
Image annotation is getting the best out of technology. The need for image annotation is inevitable, from preventing crimes to boosting agricultural initiatives and enhancing healthcare services. However, the challenge lies in tagging or labeling massive datasets. The tagged information demands the highest label of accuracy. Therefore, outsourcing image annotation services to Maxicus at an affordable price is the wise option.Categories: