Semantic Image
Segmentation Services
Get thousands of labeled images for your ML training model within a few hours. We’re here to provide you with our semantic image segmentation services. Our highly qualified human annotators accurately label images to achieve accuracy in computer vision models. We ensure data at the pixel-perfect level through our in-depth labeling and double-checked methods.
25,000+
Projects
9+ years
Experience
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Certified
15,000+
Satisfied Clients
99.99%
Accuracy
Get Pixel-Perfect Annotated Images
Semantic Image segmentation and bounding box segmentation, both are different methods of data annotation, particularly for image annotation. But, the bounding box segmentation method is not as accurate as semantic segmentation. It creates boxes to cover objects, which sometimes overlap with other boxes. Therefore, labeling data at the pixel level becomes crucial for computer vision models. So, semantic image segmentation takes objects, labels them, and makes them into single classes – no overlapping at all. In simple terms, it classifies each pixel located in an image with precise information. Note that our semantic image segmentation services accurately label ML training data in large volumes without errors.
Helping AI/ML Models to Identify Objects
Image annotation is purposefully done for developing computer vision models. It classifies and labels every pixel to help AI to identify different objects. Developing AI technology, especially with computer vision models is on trend. However, the majority of developers face many challenges regarding image segmentation. That includes drawing accurate object boundaries, occlusions, ambiguous regions, etc. To avoid these challenges, they must consider outsourcing semantic image segmentation services. We do image annotation and deliver accurate segmentation work. If you are among those developers facing these segmentation issues then you must try our solutions. We help you not only with our quality of work but also with decreasing time & cost.
Get Pixel-Perfect Annotated Images
Semantic Image segmentation and bounding box segmentation, both are different methods of data annotation, particularly for image annotation. But, the bounding box segmentation method is not as accurate as semantic segmentation. It creates boxes to cover objects, which sometimes overlap with other boxes. Therefore, labeling data at the pixel level becomes crucial for computer vision models. So, semantic image segmentation takes objects, labels them, and makes them into single classes – no overlapping at all. In simple terms, it classifies each pixel located in an image with precise information. Note that our semantic image segmentation services accurately label ML training data in large volumes without errors.
Helping AI/ML Models to Identify Objects
Image annotation is purposefully done for developing computer vision models. It classifies and labels every pixel to help AI to identify different objects. Developing AI technology, especially with computer vision models is on trend. However, the majority of developers face many challenges regarding image segmentation. That includes drawing accurate object boundaries, occlusions, ambiguous regions, etc. To avoid these challenges, they must consider outsourcing semantic image segmentation services. We do image annotation and deliver accurate segmentation work. If you are among those developers facing these segmentation issues then you must try our solutions. We help you not only with our quality of work but also with decreasing time & cost.
On-demand Semantic Image Segmentation
Services Offerings
At present, image annotation is primarily done in three ways; semantic, panoptic, and instance. We, at AskDataEntry, obtained relevant skills and expertise doing all these annotations with accuracy. Let’s check how these techniques are different and how we work to assist you with annotating image data.
Real-Life Applications of
Our Image Segmentation Annotation Service
With the help of our semantic image segmentation, you can move from R&D prototypes that are still under development to working, production-ready solutions. We know how dynamic your data training process is, and we work hard to be flexible and responsive to your requirements. Below you can find more reasons to outsource this service to us-
Self-Driving Vehicles
Accurately annotated image data helps develop computer vision models for self-driving cars. It precisely helps detect signs, distinct objects, obstacles, pedestrians, animals, and others on the road. The technology assists vehicles to navigate the distance with proper safety measures.
Social Media
Camera filters and effects on social media are created with the help of semantic image segmentation methods. Applications such as Instagram, Snapchat, etc utilize this technique to identify different objects and then add filters to them.
Geo-Sensing Satellites
Satellite images are used in tracking vast tracts of land, and measuring urbanization, deforestation, and other environmental matters. The application of semantic image segmentation services made all the processes robotic and automated. Machines are now doing all these tasks accurately.
Agro-Farm Technology
Tracking of crop fields through computerized systems is possible because of this system. The computer vision AI models automate pesticide spraying, seeding, and other processes. Through satellite imagery and drone technology, it’s also helping measure deforestation.
Medical Diagnosis
At present, the requirement for semantic image segmentation services in the medical industry is at its peak. Annotated images in medical technology help detect anomalies along with finding possible diagnoses. Plus, they are helping with the upgradation of CT scans, X-rays, MRI technology, etc.
Real-Life Applications of
Our Image Segmentation Annotation Service
With the help of our semantic image segmentation, you can move from R&D prototypes that are still under development to working, production-ready solutions. We know how dynamic your data training process is, and we work hard to be flexible and responsive to your requirements. Below you can find more reasons to outsource this service to us-
Self-Driving Vehicles
Accurately annotated image data helps develop computer vision models for self-driving cars. It precisely helps detect signs, distinct objects, obstacles, pedestrians, animals, and others on the road. The technology assists vehicles to navigate the distance with proper safety measures.
Social Media
Camera filters and effects on social media are created with the help of semantic image segmentation methods. Applications such as Instagram, Snapchat, etc utilize this technique to identify different objects and then add filters to them.
Geo-Sensing Satellites
Satellite images are used in tracking vast tracts of land, and measuring urbanization, deforestation, and other environmental matters. The application of semantic image segmentation services made all the processes robotic and automated. Machines are now doing all these tasks accurately.
Agro-Farm Technology
Tracking of crop fields through computerized systems is possible because of this system. The computer vision AI models automate pesticide spraying, seeding, and other processes. Through satellite imagery and drone technology, it’s also helping measure deforestation.
Medical Diagnosis
At present, the requirement for semantic image segmentation services in the medical industry is at its peak. Annotated images in medical technology help detect anomalies along with finding possible diagnoses. Plus, they are helping with the upgradation of CT scans, X-rays, MRI technology, etc.
Why AskDataEntry for
Semantic Image Segmentation Services
We have been witnessing the journey of AI development, especially computer vision technology. For the last 9 years, we have been directly working in the field and delivering image annotation services. Therefore, we gained a wide spectrum of expertise in annotation projects. We are not only limited to this, explore our unique advantages here.
Why AskDataEntry for Semantic Image Segmentation Services
We have been witnessing the journey of AI development, especially computer vision technology. For the last 9 years, we have been directly working in the field and delivering image annotation services. Therefore, we gained a wide spectrum of expertise in annotation projects. We are not only limited to this, explore our unique advantages here.
Timely Delgate your Image Annotation Project!
When you timely enroll in our semantic image segmentation services, you’ll get timely delivery. It’s simple. Kickstart your computer vision project with our dedicated services. We are a team of skilled image annotators that know how to do the tasks. Unlike others, we provide you with cost-friendly options for our services. Let’s fill out this form and help our team to get back to you.
Timely Delgate your Image Annotation Project!
When you timely enroll in our semantic image segmentation services, you’ll get timely delivery. It’s simple. Kickstart your computer vision project with our dedicated services. We are a team of skilled image annotators that know how to do the tasks. Unlike others, we provide you with cost-friendly options for our services. Let’s fill out this form and help our team to get back to you.
Open Communication & Responsive Support
We use the same project management apps or communication channels that your team does. Therefore, your team can easily share all the requirements directly with us without any formalities. Effective communication between the annotators and project leaders is the key to implementing a strong AI development model. We believe in collaboration for annotation work. You’ll always get responsive support from our end to address your image segmentation requirements.
Semantic Segmentation Process
Following the deep learning architecture, we segment semantic images using proper labels. We follow all the steps for performing the segmentation work.
01
Pre-processing Images
Before starting the segmentation process, we pre-process all the images for suitable analysis. We resize, reduce noise, and normalize colors to make the image input consistent and optimal.
02
Feature Extraction
After completion of pre-processing, we extract the pertinent features of the images to highlight distinct patterns, shapes, and textures.
03
Classification
Assign labels and classes to every pixel after classifying the image features. It helps ML models to distinguish between various objects.
04
Output visualization
Overlay a segmentation mask on your images to highlight classes and objects of interest. It distinguishes the identified objects from the remaining images.
Frequently Asked Questions (FAQs)
Client Experiences
AskDataEntry has provided us with excellent human gesture annotation services. The company has met all our expectations in delivering the best quality services. We totally loved the way AskDataEntry works and admire that. We hope AskDataEntry and we will collaborate like this in the future also.
Jim N., Technical Head of a Swedish Software Development Company
