Pixel-Level Semantic Segmentation Services for Deep Learning
Semantic segmentation will help AI-based perception model to classify and detect the objects of interest with pixel-wise annotation. Cogito provides semantic segmentation annotation to classify, localize, detect and segment multiple types of objects in the image belongs to a single class.
Image Segmentation for Deep Learning
Semantic segmentation in image annotation makes multiple objects detectable through instance segmentation helps computer vision to localize the object. It can visualize the different types of object in a single class as a single entity, helping perception model to learn from such segmentation and separate the objects visible in natural surroundings.
Precise Movement of Self-driving Cars
Autonomous vehicles working on computer vision-based deep learning perception model can learn better scenario through more accurate pixels to recognize the different class of objects on road. While developing a self-driving car, it is providing the crucial information to make sure it can move safely avoiding all types of objects in the path.
Accurate Aerial Imagery View for Monitoring
Train your drone or autonomous flying objects for geosensing of farming fields, urbanization and deforestation through image segmentation deep learning. Satellite imagery annotated precisely here for monitoring such fields and gather the useful information to improve farming efficiency and enhance the crop productivity.
Instance Segmentation for Deep Learning
To enable more dense detection for computer vision, image segmentation process takes object detection a step further. Yes, instance segmentation helps to detect the objects within the defined categories by creating the masks for each individual object in the image. It is just like semantic, but dives a bit deeper and identifies, for each pixel of the object instance it belongs to. Cogito offers annotation for instance segmentation deep learning algorithms.
Panoptic Segmentation Datasets for AI
To make the object detection process easier and accurate, panoptic segmentation is used to annotate the images containing objects of a single class. Actually, it is the combination of instance and semantic segmentation. In this annotation technique annotators classify all the pixels in the image as belonging to a class label, while identifying what instance of that class they belong to. Cogito provides panoptic segmentation dataset for all types of complex AI models.
Semantic Segmentation for Medical Images
Not only automotive, robotics and autonomous flying, but semantic segmentation also provides the accurate information of medical diagnosis through semantic segmentation medical images. Cogito is specialize in healthcare training data by offering medical image annotation service to diagnosis different types of diseases.