Average Ratings 0 Ratings

Total
ease
features
design
support

No User Reviews. Be the first to provide a review:

Write a Review

Average Ratings 1 Rating

Total
ease
features
design
support

Description

In various types of figures, such as western blots, microscopy images, and light photography, we identify inappropriate duplication and manipulation. Imagetwin serves as a robust tool in the peer-review process, automatically flagging various integrity issues that can be swiftly verified by reviewers. A notable number of academic papers are found to have image-related concerns, including manipulation and plagiarism. Although automated text plagiarism detection tools have become commonplace, similar solutions for image integrity have been lacking until now. The manual verification of images for such issues is not only labor-intensive and costly but also hampered by a shortage of qualified professionals, leading to many integrity problems going unnoticed. Implementing Imagetwin could significantly enhance the efficiency and accuracy of image assessments in academic publishing.

Description

Scikit-image is an extensive suite of algorithms designed for image processing tasks. It is provided at no cost and without restrictions. Our commitment to quality is reflected in our peer-reviewed code, developed by a dedicated community of volunteers. This library offers a flexible array of image processing functionalities in Python. The development process is highly collaborative, with contributions from anyone interested in enhancing the library. Scikit-image strives to serve as the definitive library for scientific image analysis within the Python ecosystem. We focus on ease of use and straightforward installation to facilitate adoption. Moreover, we are judicious about incorporating new dependencies, sometimes removing existing ones or making them optional based on necessity. Each function in our API comes with comprehensive docstrings that clearly define expected inputs and outputs. Furthermore, arguments that share conceptual similarities are consistently named and positioned within function signatures. Our test coverage is nearly 100%, and every piece of code is scrutinized by at least two core developers prior to its integration into the library, ensuring robust quality control. Overall, scikit-image is committed to fostering a rich environment for scientific image analysis and ongoing community engagement.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Akira AI
Cython
Label Studio
MLReef
PostgresML
Python
Yamak.ai
Yandex Data Proc
ZenML

Integrations

Akira AI
Cython
Label Studio
MLReef
PostgresML
Python
Yamak.ai
Yandex Data Proc
ZenML

Pricing Details

€25 one-time payment
Free Trial
Free Version

Pricing Details

Free
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Imagetwin

Founded

2022

Country

Austria

Website

imagetwin.ai

Vendor Details

Company Name

scikit-image

Country

United States

Website

scikit-image.org

Product Features

Product Features

Alternatives

Scopus Reviews

Scopus

Elsevier

Alternatives

Ovid Reviews

Ovid

Wolters Kluwer
imgix Reviews

imgix

Zebrafish Labs