Search Results for "mii-tool"
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Showing 6 open source projects for "mii-tool"
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MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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1
Computer Vision Annotation Tool (CVAT)
Interactive video and image annotation tool for computer vision
Computer Vision Annotation Tool (CVAT) is a free and open source, interactive online tool for annotating videos and images for Computer Vision algorithms. It offers many powerful features, including automatic annotation using deep learning models, interpolation of bounding boxes between key frames, LDAP and more. It is being used by its own professional data annotation team to annotate millions of objects with different properties. -
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Label Studio
Label Studio is a multi-type data labeling and annotation tool
The most flexible data annotation tool. Quickly installable. Build custom UIs or use pre-built labeling templates. Detect objects on image, bboxes, polygons, circular, and keypoints supported. Partition image into multiple segments. Use ML models to pre-label and optimize the process. Label Studio is an open-source data labeling tool. It lets you label data types like audio, text, images, videos, and time series with a simple and straightforward UI and export to various model formats. ... -
3
Email to Event - ETE
The python App/Skrypt automaticly add important events into calendar.
It is use AI running localy and model you can choose. Skrypt have a tool for automatic add to scheduler. It now not working with Microsoft outlook and Google gmail, for certifications and API polici reasons . Fuly tested on Seznam.cz* services, if you have difrent provier with same type of security it will be working. *Email is using standart IMAP, Calendar use iCalendar API and authentification method. -
4
Acharya
A Data Centric annotation tool for your Named Entity Recognition
A data-centric annotation tool to increase the accuracy of your Named Entity Recognition projects which helps rapidly identify and fix labeling errors in your dataset. Import/export datasets in multiple formats, train a model and use it to aid in the annotation process. Setup an MLOps pipeline to experiment with different algorithms on the same data and increase their accuracy and performance in a data-centric way. -
Enterprise-grade ITSM, for every businessFreshservice is an intuitive, AI-powered platform that helps IT, operations, and business teams deliver exceptional service without the usual complexity. Automate repetitive tasks, resolve issues faster, and provide seamless support across the organization. From managing incidents and assets to driving smarter decisions, Freshservice makes it easy to stay efficient and scale with confidence.
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5
Compose
A machine learning tool for automated prediction engineering
Compose is a machine learning tool for automated prediction engineering. It allows you to structure prediction problems and generate labels for supervised learning. An end user defines an outcome of interest by writing a labeling function, then runs a search to automatically extract training examples from historical data. Its result is then provided to Featuretools for automated feature engineering and subsequently to EvalML for automated machine learning. -
6
Speechalyzer
Process large speech data wrt transcription, labeling and annotation
Speechalyzer: a tool for the daily work of a 'speech worker' It is optimized to process large speech data sets with respect to transcription, labeling and annotation. It is implemented as a client server based framework in Java and interfaces software for speech recognition, synthesis, speech classification and quality evaluation. The application is mainly the processing of training data for speech recognition and classification models and performing benchmarking tests on speech-to-text, text-to-speech and speech classification software systems.
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