Data Annotation Services
Improve the efficiency of your AI models with accurate annotation of text, image, audio, and video data. Our data annotation service includes adding annotations or metadata to raw data using various techniques, enabling AI models to identify patterns, relationships, and meanings in the data. We excel in generating top-tier AI training data, ensuring precision and quality control during the model training phase.
CHOOSE THE RIGHT DATA ANNOTATION COMPANY
Bluebash offers data annotation services tailored to each client's specific needs. Our primary labeling services include top-notch text, video, audio, and image annotation. Bluebash team collaborates with clients to customize processes, ensuring the validation of annotation work meets their quality standards. Our skilled subject matter experts swiftly deliver all annotation tasks with precision.
Our Data Engineering Services
Image Annotation
Leveraging advanced techniques such as bounding boxes, polygon annotation, key point annotation, LiDar, semantic segmentation, semantic annotation, and image classification, our AI experts meticulously label both general and industry-specific images. Every pixel of an image is scrutinized to ensure high-quality results.
Video Annotation
With proficiency in video footage labeling, we efficiently train computer vision models for object detection and identification. Our diverse video annotation techniques, including bounding boxes, polygon annotation, key point annotation, and semantic segmentation, cater to various industries, supporting applications like self-driving cars, drones, and robotics.
Text Annotation
Our text annotation service aids tasks such as sentiment analysis, intent analysis, and named entity recognition (NER) which is tailored for natural language processing and machine learning models. Our expert team utilizes advanced annotation tools and techniques to annotate large data volumes swiftly and efficiently, saving businesses time and resources.
Audio Transcription and Annotation
Unlocking the full potential of audio data, our service provides transcription and annotation for applications like market research and speech recognition. We convert audio content into machine-readable text and label it for tasks such as named entity recognition, sentiment analysis, and conversation categorization.
Data Annotation Techniques We Use
Here are the data annotation techniques we utilize to ensure accuracy and quality control throughout the AI training data development process
Bounding Boxes
This technique is employed to annotate data in fields like machine learning, robotics, autonomous vehicles, and retail, accurately classifying objects in images and videos.
3D Cuboid Annotation
Utilizing the 3D cuboid model technique, we enable the model to grasp the object’s shape, size, and orientation for more informed decision-making.
Landmark Annotation
This technique identifies specific points on natural objects such as faces, aiding in determining emotional characteristics and facilitating highly targeted marketing campaigns for personalized customer experiences.
Skeletal Annotations
Through skeletal annotation, we curate extensive datasets of annotated skeletal images, training machine learning algorithms for more efficient and accurate medical diagnoses.
Polygon Annotation
Using polygon annotation, we create intricate outlines around objects in videos and images, simplifying the identification and localization of specific products.
Semantic Segmentation
By employing semantic segmentation, we overcome the visual limitations of legacy computers, enhancing their ability to interpret 2D image data and providing users with a more detailed understanding of image content.
3D Point Cloud Annotation
Training models with 3D point cloud annotation improves accuracy and detail in object detection and classification, offering customers more precise measurements of dimensional attributes for enhanced performance and decision-making.
Polyline Annotation
Polyline annotation enables autonomous cars and other mobile technologies to detect and follow lane markings on roadways effectively, enhancing safety and reliability.
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