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Semantic Segmentation

Meaning & Importance

Semantic segmentation refers to the method of linking every pixel in an image to a class label. Labels can be cars, flowers, persons etc. any object included. Different objects get labeled in different colors with semantic segmentation tools. For example, an image has various cars. So, the segmentation will label the sedan cars in red and SUVs in white, according to classification of cars.

Another term related to semantic segmentation is the instance segmentation which separately labels the objects belonging to the same class. Semantic segmentation services provided by us with proper implementation of tools lets machines discern one region of an image with another, according to the semantic context of the region. Images can be processed and analyzed using AI semantic segmentation.

Webtunix develops semantic segmentation tools for different areas of applications like robotics, photo editing tools, autonomous vehicles and human-computer interaction systems. Semantic segmentation is essential to make models understand the context in the environment in which they operate.

Examples of Semantic Segmentation

  • Self-driving cars: Semantic segmentation here lets cars know the location of another car or person on the road.
  • Robotic Systems: This method helps robots know the location of their other parts and adds a boost of performance.
  • Damage Detection: The extent of the damage caused to a vehicle or any object can be easily known with semantic segmentation.

Applications & Uses of Semantic Segmentation

Facial Segmentation: By implementing this method in computer vision (CV) systems, tasks like age recognition, gender prediction, gender ethnicity and expression on recognitions etc. are easily achieved. These are done by separating the face regions like mouth, eyes, nose, chin, hair etc. Webtunix uses proper semantic segmentation and perfects the other factors in image too like lighting conditions, feature occlusion, image resolution, orientation etc.

Fashion Categorization: It becomes difficult for machines to classify and recognize clothes, accessories etc. Here, we take semantic segmentation into action to do the task for you accurately. Our team implements smart algorithms and takes each and every variable into consideration. From small objects to large ones, everything is classified with perfection by the models created by us.

Bio-medical Image Diagnosis: Diagnose specialists fail in precise analysis of the medical charts due to overlapping or complexity of medical images. This method performs classification, makes the diagnostic tests simpler and generates results quicker.

Autonomous Driving: Self-driving is an extremely complex task that requires real-time analysis, perception and action. Semantic segmentation helps the autonomous vehicles identify objects like traffic signals, lanes, pedestrians etc. any obstruction that meets on the way.

Satellite Image Processing: Satellite image processing covers a large geographical area and that too with many objects included. The technique helps satellites do the correct analysis of what's on land and on the objects that are necessary. We use this method in our precision agriculture and geofencing services.

Webtunix AI offers services data annotation for semantic segmentation. We ensure to provide best in-class semantic segmentation computer vision research and related services with promised on-time delivery, quality assurance and as per your project requirements.