Semantic Segmentation

Auto semantic segmentation by OCLAVI Predict TM αlpha which is a state-of-the-art model to annotate pixel-level image segmentation.

Our image annotation solution empowers you to perform semantic segmentation with unparalleled precision and quality, which is indispensable for creating advanced computer vision models that can accurately identify and classify objects and regions in images, opening up a whole range of exciting applications and possibilities.

Accurate Object Detection and Localization

The detailed and comprehensive understanding of the image content provided by OCLAVI allows machines to better distinguish between objects, even when they have similar colors and textures.

By segmenting an image at the pixel-level, machines can accurately identify and locate objects, making semantic segmentation a powerful tool for various computer vision applications, such as object detection, scene understanding, and image and video editing.

Robustness

Our tool can handle a variety of image variations such as changes in lighting conditions, camera angle, and viewpoint, making it a robust technique for image analysis.

Automatic Image Annotation

OCLAVI can help to automatically annotate images with semantic labels, making it easier to search and retrieve images based on their content.

Medical Imaging

Helps to improve the accuracy and efficiency of medical imaging analysis, aiding in disease diagnosis, treatment planning, and medical research.

It can also enable more accurate and precise image-guided interventions, such as surgeries, to help guide the doctors and accurately locate and remove diseased tissue.

Drone Imaging

Obtain a thorough and comprehensive understanding of their surroundings, through OCLAVI's semantic segmentation tool, thereby enhancing their ability to perform a diverse set of tasks with greater precision and effectiveness.

It can also be used in search and rescue operations, enabling drones to detect and locate individuals in emergency situations.

Autonomous Vehicle

Enables AVs to understand and interact with their environment more effectively, resulting in improved safety and efficiency in autonomous driving.

This tool can be used to detect and recognize traffic signs and signals, enabling AVs to obey traffic laws and navigate intersections safely.