Image Annotation Outsourcing

Our fully managed humans provide a data labelling service solution on google cloud platform. They create a data set for use in your A.I., machine learning or NLP project. With a goal of 100% accuracy.

We can generate highly accurate labels because of our strict internal processes. These include, re-training, variances, spotting potential errors in gold-sets and refining definitions.

We have experience with AI platform data and software like Kubernetes engine



We at iSuporta, are committed to providing you with the highest quality data labeling services so that you can build successful AI, machine learning, and NLP.

What is Data Labeling?

According to WikiPedia D/L are a group of samples that have been tagged with labels, basically it is the building blocks of any AI Project. In where the AI software finds patterns and similiarities so it can define future un-labeled data in accordance with it’s self defined pattern structure.

Data Labeling is very helpful when organizing and managing large data sets. It can also be used to improve the quality of the data sets to make sure it’s accurate and consistent. This is also used to make training datasets for machine learning work, with the following methods

  • Anomaly Detection – identifying unusual data patterns for fraud, intrusion and process control.

  • Artificial Neural Network – Models complex data, regression, classification, prediction etc

  • Reinforcement Learning – gamification of learning, earning points for success and punishment for failure

  • Learning with Humans – Human assisted learning for AI is what we specialize in

  • Supervised Learning – watched by humans or software to confirm proper path

  • Clustering – groups similar data together for prediction of data analysis.

  • Dimensionality Reduction – reduction of large data used to see patterns and manageability of data

  • Structured Prediction – for NLP and Vision very accurate for prediction of events

“Learn and Use AI,  before your competitors Know and Use AI.”

Andrew Karpaty, Tesla

100% Focus on details of your AI, ML, NLP Data Labeling Project.

Great Equipment

Tools of the trade do make a huge difference between some or a lot of detailed work to be done. Professional Data Labeling requires big screens, fast internet and good computers.

High Throughput

Time is money, and getting tasks completed is also key to success, with most datasets in the 100”s of millions, there is no time to spare, especially getting to market.

Constant Training

Professionals must constantly sharpen their skills, as humans we slack over time, but to train AI, 100% correct detail is crucial to success of your data set.

Data Labeling Software Tools must fit Data Labeling Tasks

Image annotation companies have experience showing that not all annotating talks are the same. If it’s Data Labeling for AI, or Labelbox video annotation, , NLP, Hive or Medical, we will work on the best solution for you.

Video Annotation

Video Annotation

Annotating the real world of cars and traffic

Classification

Medical Procedure

Text &Data

Image Annotation

Retail Shelf

Text & Document

Categorization

Choose the Right tool for the job

Label Box

Catalog

Deepen AI

Anotate

AWS

Model

Data Loop

Boost

Industries in need of high accuracy datasets

We focus on high level of accuracy, with internal training programs, and knowledge share, to make your Artificial intelligence (AI), Machine Learning (ML), and Natural Language Processing (NLP) project a success.

Retail Shelf Stocking

Farming Crop Monitor

Product Categorize

Automotive Self Driving

Legal - Text Decipher

Security - Monitoring

Choose the Right tool for the job

Data Matching

Data matching is the process of comparing two different sets of data to verify if there is any data that refer to the same entity

De Duplicate

Post-processing dedupe is an asynchronous backup process that removes redundant data after it is written to storage

Categorize

AI classifications works when the business feeds the AI data points, such as product stock, along with their predetermined categories

Content Moderation

online platform screen and monitor user-generated content based on platform-specific rules and guidelines

Data Enrichment

enhancing data info received from external sources augmenting existing datasets to improve quality of the conclusions from the data

Data Extraction

the process of procuring data from a given source and moving it to a new context, either on-site, cloud-based

Data Mining

nontrivial extraction of implicit, previously unknown and potentially useful information from data

Intent Analysis

new wave and evolution in NLP and AI that is all set to change how customer feedback is evaluated

Audio Transcription

convert human speech into text.

Sentiment Analysis

field of study that uses computational methods to analyze, process, and reveal people’s feelings, sentiments

Entity Classify

Entities can be fields, data, or text describing just about anything — a time, place, person, item, number, etc

Bounding Boxes

made-up square that serves as a guideline point for object recognition and creates a collision box for that element

Polygon Annotation

recise way to annotate objects by selecting a series of x, y coordinates along its edges

Semantic Segment

Segmenting each pixel in an image within its region that has semantic value with a specific label.

Lidar Annotate

An essential sensor for geospatial technology, autonomous technology, and many other industry applications

Panoptic Segment

an image segmentation task that combines the prediction from both instance and semantic segmentation into a general unified output

The Labelers is of Key Importance. They must be trained, retrained, Quality assured, tested, and verified.

We have achieved success in Data Labeling mainly because we focus on the specific employees.   We remove the bottom 10% and reward the top 10%.    They are constantly trained and are cmopelled to show discrepancies and record them and report them to the client.   We know how valuable a 100% accurate data set is.  This is what we strive for, so your project is a success.

Data Labeling F.A.Q.

People Also ask us these questions, maybe they can help.

Data labeling is the process of describing and attaching information in a structured way, in order to create an organized data set which groups large numbers of data points into small numbers of categories. This is often used for teaching an AI to know that minor differences still mean the same thing. For example, a bicycle picture from the left and from the right, are the same thing. If there are millions of pictures (data points) looking similar to a bicycle, the AI can be trained to define a bicycle as a bicycle just because it resembles it’s data set.

the differenece between annotation and labeling is mainly the same, but, annotating is usually referred to in text forms, while data labeling can be all forms, of video, data, sound, text, pictures, etc..

A good data labeler is a person who can think fast, can see patterns easily, good eyesight, and can focus for long periods of time on a task.

Annotation & Data Labeling Resources

Great Resources here from MIT

Some more AI training info from Stanford U

Medical Labeling and Annotation Paper HERE

Find a great Free tool to train and label your data HERE

Important Links

Recent Posts

Office Address

  • Unit 901 The Insular Life Cebu Business Center Mindanao Ave. corner
    Biliran Rd Cebu City 6000 Philippines

  • Level 9 MSY Tower Pescadores Road
    Cebu Business Park Cebu City 6000