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What is Avizo Software?

Thermo Scientific Avizo Software is recognized as a versatile and reliable tool for 3D visualization, analysis, and measurement of essential features obtained from imaging datasets, enabling both researchers and engineers to convert multi-dimensional microscopy and CT images into actionable insights. It caters to a wide array of applications, ranging from innovative materials research to fully automated quality assurance and control processes, which equips users with the ability to extract valuable insights into materials and processes by turning complex image data into measurable parameters and significant interpretations. The software boasts sophisticated features like AI-enhanced image segmentation, improvement, denoising, and traditional analysis tools, which guarantee accurate measurement and interpretation of vital sample characteristics. Moreover, it facilitates the overlay and registration of diverse imaging and spectroscopy data types, regardless of their format or resolution, promoting a detailed visualization of results in multi-channel mode for correlative analysis. This enhanced functionality significantly deepens the understanding of intricate datasets while also expanding the horizons of exploration in the realm of scientific research. As a result, researchers can uncover new relationships and patterns that were previously obscured, further propelling innovation in their respective fields.

What is Atinary SDLabs Platform?

Atinary's Self-Driving Labs (SDLabs) platform provides a no-code approach for artificial intelligence and machine learning, designed to revolutionize research and development workflows by enabling traditional laboratories to transition from manual experiments to fully autonomous experimentation. This innovative platform bolsters the design and improvement of experiments through a robust closed-loop system that integrates AI-generated hypotheses, predictions, and decision-making processes. Among its key functionalities are multi-objective optimization, effective database management, seamless workflow orchestration, and immediate data analysis. Users can define experimental parameters with specific limitations, allowing machine learning algorithms to guide the subsequent phases of the process, carry out experiments either manually or with robotic assistance, evaluate results, and refresh models with the most recent data, thereby accelerating the journey toward more efficient, cost-effective, and environmentally sustainable products. Furthermore, Atinary provides exclusive algorithms such as Emmental for addressing non-linear constrained optimization challenges, SeMOpt for facilitating transfer learning within Bayesian optimization, and Falcon, all of which significantly boost the platform's capabilities and performance. By utilizing these sophisticated tools, researchers are empowered to enhance their experimental workflows, fostering greater efficiency and driving innovation in their fields. Ultimately, the SDLabs platform represents a transformative shift in how laboratories approach experimentation, paving the way for groundbreaking discoveries.

Media

Media

Integrations Supported

Additional information not provided

Integrations Supported

Additional information not provided

API Availability

API Availability

Pricing Information

Pricing not provided
Free Trial Offered?

Pricing Information

Pricing not provided

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

Web-Based Support

Customer Service / Support

Standard Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training

Training Options

Documentation Hub
On-Site Training

Company Facts

Organization Name

Thermo Fisher Scientific

Date Founded

2006

Company Location

United States

Company Website

www.thermofisher.com/mx/es/home/electron-microscopy/products/software-em-3d-vis/avizo-software.html

Company Facts

Organization Name

Atinary

Date Founded

2019

Company Location

Switzerland

Company Website

atinary.com/solutions/

Categories and Features

Materials Science

Not specified

Categories and Features

Materials Science

Not specified

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