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What is Sixgill Sense?

The entire machine learning and computer vision workflow is simplified and accelerated through a unified no-code platform. Sense enables users to design and deploy AI IoT solutions in diverse settings, whether in the cloud, on-site, or at the edge. Learn how Sense provides simplicity, reliability, and transparency for AI/ML teams, equipping machine learning engineers with powerful tools while remaining user-friendly for non-technical experts. With Sense Data Annotation, users can effectively label video and image data, improving their machine learning models and ensuring the development of high-quality training datasets. The platform also includes one-touch labeling integration, which facilitates continuous machine learning at the edge and streamlines the management of all AI applications, thus enhancing both efficiency and performance. This all-encompassing framework positions Sense as an essential asset for a variety of users, making advanced technology accessible to those with varying levels of expertise. Additionally, the platform's flexibility allows for rapid adaptation to evolving project requirements and fosters collaboration among teams.

What is LabelMe?

LabelMe is designed as a web-based platform that enables users to annotate images, thereby assisting in the development of image databases vital for research in the field of computer vision. Through its annotation tool, users can play an integral role in expanding this growing database. Images can be arranged into organized collections, and users have the option to create nested collections similar to traditional folder structures. When downloading their database, users will find that the arrangement of collections mirrors this folder organization. Additionally, users can upload their images to these collections and annotate them using the LabelMe tool. There are also unlisted collections that can be accessed by anyone with the specific URL, even though they remain hidden from public view. Ultimately, LabelMe strives to make both images and annotations freely available to the research community, promoting collaboration and fostering innovation. This dedication to open access underscores the significance of shared resources in propelling advancements in computer vision research, while also encouraging diverse contributions from various users.

Media

Media

Integrations Supported

Check Point IPS
Check Point Infinity
ThreatStream

Integrations Supported

API Availability

Has API

API Availability

Pricing Information

Pricing not provided
Free Version

Pricing Information

Pricing not provided

Supported Platforms

SaaS
Windows
Mac
On-Prem
Linux

Supported Platforms

SaaS

Customer Service / Support

Standard Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub

Training Options

Documentation Hub

Company Facts

Organization Name

Sixgill

Date Founded

2007

Company Location

United States

Company Website

sixgill.com

Company Facts

Organization Name

LabelMe

Company Website

labelme.csail.mit.edu/Release3.0/

Categories and Features

Data Annotation

Not specified

Data Labeling

Labeling Automation
Labeling Quality
SDK
Task Management
Team Collaboration

Image Annotation

Not specified

IoT

Not specified

Machine Learning

Not specified

Video Annotation

Not specified

Categories and Features

Image Annotation

Not specified

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