Image Processing and Artificial Intelligence.

Images are a source of information used for decision-making in fields such as medicine, security, agriculture, transportation management, and more. However, utilizing such data to its full extent without computer programs is challenging and not always feasible, as it requires a significant amount of time and human resources to process the information.

The revolution in the use of visual materials has begun with the help of AI, which is capable of quickly and accurately analyzing images and providing information for decision-making. Currently neural networks can perform a variety of image processing tasks, including processing photographs, snapshots, drawings, and diagrams.

What tasks is artificial intelligence used for in image processing?

1. Object recognition and clustering: AI can identify objects in photographs, pictures, and diagrams, such as cars, wardrobe items, mechanical parts, and machines.

2. Object detection and localization: AI can find objects in images and mark them with bounding boxes, labels, etc. This is applied in autonomous transportation applications, video surveillance systems robotics.
3. Semantic segmentation: distinguishing multiple groups, such as pedestrians, cars, trees, etc.

4. Image captioning: AI can understand the essence of an image and generate a description for it.
5. Enhancing the quality of low-resolution images.
6. Generating images based on templates, styles, and examples.
7. Image restoration and improvement through element elimination, color adjustment, or filling in missing fragments.
8. Image transformation, for example, from 2D to 3D format. A similar project has been implemented by the Epol Soft team.
9. Image moderation: AI can analyze content and remove unwanted content to comply with safety rules.

The list of AI-based tools for image processing is constantly expanding, and solutions for new applications in various industries and fields emerge.

Which industries is artificial intelligence used in for image recognition?

1. Healthcare: diagnosis and remote patient monitoring, where patients can take photos and send them for AI processing.
2. Transportation sector for obstacle detection and recognition of road signs by autonomous vehicles.
3. Security: Image processing is necessary for tracking and recognizing objects and people. Neural networks can quickly analyze thousands of images and identify faces and objects.
4. Manufacturing for detecting defects and automatic quality control. For example, high-resolution photos of auto parts are analyzed using neural networks to detect scratches, cracks, or misalignments.
5. Agriculture for optimizing the use of fertilizers and irrigation systems. Cameras are installed on equipment, and based on the images, AI determines the needs of each plant for fertilizers and moisture and adjusts the application accordingly.
6. Social networks, where a large amount of content is generated, requiring fast image processing for moderation. Artificial intelligence can promptly identify unwanted content.
7. Education: AI can simulate real-world objects for practicing skills in fields such as medicine, piloting, etc. For example, based on X-ray images, neural networks generate a 3D model of a jaw that is loaded into a simulator for training dentists. More details about the project can be found at this link.

The use of AI expands the boundaries of utilizing visual materials for various tasks and purposes, transforming images, photographs, videos, and snapshots into a real-time source of information.