Semantic Segmentation Services
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Semantic Segmentation has always been a point of issue in computer vision industry. As, it gets difficult to identify ‘what’s in a image?’ for a computer vision company, they outsource the services of semantic segmentation. And, here’s when Ortuse can come to your help.
Semantic segmentation is a typical way of locating edges and gradients and is considered advanced computer vision task. Our team of experts can help you save time and man power in semantic segmentation. Classification is about assigning a single class or metadata to an entire image. In semantic segmentation, pixels of an image are classified into different classes.




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Approaches of Semantic Segmentation
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Region-Based Segmentation
The easiest way to segment different objects in an image can be using their pixel values. The pixel values are usually different for the objects and the background of the image, in case there is a sharp contrast between them. Our team will separate the objects into distinct regions on the basis of certain threshold values.
Edge Detection Segmentation
The edge detection approach of semantic segmentation is to detect edges of objects and boundaries between the background of the image and objects. It works well for images with better contrast between the objects. If your image consists of too many edges, edge detection segmentation might not be a good option for you. At Ortuse, we thoroughly analyze the images and other associated parameters before deciding the right approach of semantic segmentation.
Cluster-Based Semantic Segmentation
The segmentation on the basis of clustering divides the image pixels into homogenous clusters. This way, it works perfectly on small datasets and develops ultimate clusters. The process is quite expensive and the time of computation is also high. Our experts in semantic segmentation can help carry our the process successfully getting your good results for your money.
Our Goal of Semantic Segmentation
The main goal of semantic segmentation is labeling each pixel of an image with the respective class. We predict for each pixel in the target image. The process is called dense prediction, which we carry out with complete preciseness, ensuring you receive timed and fine-grained results, meeting your expectations. The result of semantic segmentation is a set of segments that together comprise a set of contours or the entire image.
Want to outsource the task of semantic segmentation from a reliable and expert team? Ortuse can be your trusted supporter in the process.
Reach us to discuss your detailed requirement.

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June 2008
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February 2010
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June 2013
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February 2018
Agencify started
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