Data Annotation and Labelling
We segment and annotate the data which feeds into and empowers client algorithms. Starting from text, image and video annotation to creating ground truth datasets for developing efficient machine learning models, we streamline people and quality processes for the extraction of structured insights from massive volumes of unstructured data.
We offer high-quality text sourcing and annotation services which encompasses of text alignment, segmentation and rectification, OCR, content area and line annotation, simple and complex table annotation, clickable item and other complex annotation types. Our entire gamut of language services also includes sourcing, printing, scanning, transcriptions and development of huge data repositories for various ML requirements.
- Scale up of text annotation services from English to 12 other foreign languages by on boarding an expert team of language specialists in French, German, Spanish, Portuguese, Italian, Russian, Persian, Korean, Mandarin, Lebanese, Chinese, Japanese, etc.
- Text Annotation of various format of texts including letters, numeric, etc. as well as various modes of text such as print, handwriting, text in videos, etc.
- Text annotation of 5000 pages of text per day with 96 – 98% accuracy
- Text sourcing and preparation of huge data repository for various ML requirements
- Text annotation of various types of text including dense texts, forms, etc. procured from various domains including Banking, Financial, Legal, Healthcare, Government, Science, Academic, etc.
Image / Video Annotation
We offer image annotation services to annotate all types of images with precise capturing tools thereby ensuring that the images are recognizable for machines or computer vision. Our advanced video annotation services also help our clients build comprehensive video datasets. AI Workspace is equipped with the experience and technology necessary to serve various kinds of image and video annotation needs of clients, and can thereafter be used across diverse industries and use cases in the AI and ML industry.
- Providing image/video annotation services for various industries and domain use cases which include:
Race and Ethnicity,Brands and Logos,Landmarks and Monuments,Cartoons and Animations,Facial Expression and Emotions,Sports and News,Person Tracking,Content Moderation,Celebrity Recognition,Anomaly Detection
Printing and Scanning
We have a dedicated team of resources allocated to printing and scanning of large sets of documents in varied fonts and resolutions for advanced machine learning towards effective text extraction.
Audio Transcription is the process of converting speech into text, wherein jargons of meaningful data is extracted through spoken words on video and audio recordings. AI Workspace offers scalable, reliable and high quality one-way and two-way audio-video communication transcription in high volumes.
Our data repository stores large volumes of data categorically. With an aid of these diverse datasets our clients are able to source raw data as and when needed and utilize the same for various effective machine learning projects.
Case Study : Boundary Boxing
This activity involves drawing a box around an image or object which has been provided.
CASE STUDY : Celebrity Recognition
This requires identifying a given celebrity in a video or image. Answers are predefined and the worker needs to select the correct answer based on the image match.
CASE STUDY: Video Decisions
The activity involves making a decision on whether the question asked is applicable for the shown video or not. The answers are pre-defined and the worker needs to select the correct answer.
CASE STUDY : Face Detection
In this activity the worker needs to draw a box tightly around a face. Various rules apply for the box to be drawn, which are given from time to time.
CASE STUDY : Text Annotation
This activity requires identification of all texts in a presented image, and drawing of boxes around the same.
CASE STUDY : Person Tracking
This job requires a box to be drawn around every person who is seen in a given video. Each frame in the video needs to be checked for such a person and a box needs to be drawn.