Search Results for "crf"
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Showing 30 open source projects for "crf"
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HubSpot is an AI-powered customer platform with all the software, integrations, and resources you need to connect your marketing, sales, and customer service. HubSpot's connected platform enables you to grow your business faster by focusing on what matters most: your customers.
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Chat with your business data with Looker. More than just a modern business intelligence platform, you can turn to Looker for self-service or governed BI, build your own custom applications with trusted metrics, or even bring Looker modeling to your existing BI environment.
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CRF-Planner
A Lightweight Planner App for Windows
A lightweight planner built for windows. Features full customizability in theme and text. Built mainly for students as a simple and easy to use planner. Email questions or concerns to me at cooperbrown@CooperBrowns.com. -
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ktrain
ktrain is a Python library that makes deep learning AI more accessible
ktrain is a Python library that makes deep learning and AI more accessible and easier to apply. ktrain is a lightweight wrapper for the deep learning library TensorFlow Keras (and other libraries) to help build, train, and deploy neural networks and other machine learning models. Inspired by ML framework extensions like fastai and ludwig, ktrain is designed to make deep learning and AI more accessible and easier to apply for both newcomers and experienced practitioners. With only a few lines... -
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Esegui SB
Bash script for video encoding & trimming with FFmpeg & EDL
This script was built to streamline and automate video encoding for various formats supported by FFmpeg while also removing commercials from TV recordings using EDL files. It can generate videos in MKV and MP4 formats (or any other format supported by FFmpeg), employ video codecs such as AV1, H.264_nvenc, HEVC_nvenc, x264, x265, and VP9, utilize the libfdk_aac audio codec, retain subtitles and implement the Constant Rate Factor (CRF) for video encoding. Read the file README for detailed info. -
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MITRE Annotation Toolkit
A toolkit for managing and manipulating text annotations
... entity identification, de-identification of medical records). The goal of MAT is not to help you configure your training engine (in the default case, the Carafe CRF system) to achieve the best possible performance on your data. MAT is for "everything else": all the tools you end up wishing you had. -
With the world of work changed forever, it’s essential to manage your workplace and assets together to effectively create a high-performing environment. The Eptura experience combines the power of workplace management software with asset management, enabling you to effectively operate your building and facilitate hybrid work.
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TFKit
Handling multiple nlp task in one pipeline
TFKit is a tool kit mainly for language generation. It leverages the use of transformers on many tasks with different models in this all-in-one framework. All you need is a little change of config. You can use tfkit for model training and evaluation with tfkit-train and tfkit-eval. The key to combine different task together is to make different task with same data format. All data will be in csv format - tfkit will use csv for all task, normally it will have two columns, first columns is the... -
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anaGo
Bidirectional LSTM-CRF and ELMo for Named-Entity Recognition
anaGo is a Python library for sequence labeling(NER, PoS Tagging,...), implemented in Keras. anaGo can solve sequence labeling tasks such as named entity recognition (NER), part-of-speech tagging (POS tagging), semantic role labeling (SRL) and so on. Unlike traditional sequence labeling solver, anaGo doesn't need to define any language-dependent features. Thus, we can easily use anaGo for any language. In anaGo, the simplest type of model is the Sequence model. Sequence model includes... -
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FFMPEG-Raspberry + PHP-FFMPEG
Install FFMPEG on Raspbian
... -c:v libx264 -preset superfast -crf 30 -c:a aac "$out${i%.*}.mp4" -y; done rm -f *.* chown -c www-data:www-data /var/www/outputvideo/*.mp4 ======= End Script ======= sudo chmod +x /usr/local/sbin/convert Make sure bash script working Put vidoe file on $input sudo convert Now put php script on your php upload script shell_exec('convert >> /dev/null 2>&1 &') Enjoy... -
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... file size. 4. Support iphone,ipod multimedia file formats. 5. Picture converting supports Zoom,Rotate/Flip,tags. 6. DVD Ripper. 7. Supports 69 languages. What's new in this version: Version 4.0: 1 Added HEVC(H265) codec in MP4,MKV; 2 Improved the algorithm of default bitrate; 3 AVC,HEVC,DIVX support codec CRF mode; 4 Updated some codecs and decodecs to latest version.
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Ansj Chinese word segmentation
Ansj word segmentation
The real java implementation of ict. The word segmentation effect is faster than the open source version of ict. Chinese word segmentation, name recognition, part-of-speech tagging, user-defined dictionary. This is a java implementation of Chinese word segmentation based on n-Gram+CRF+HMM. The word segmentation speed reaches about 2 million words per second (tested under mac air), and the accuracy rate can reach more than 96%. At present, it has realized the functions of Chinese word... -
BigQuery Studio provides a single, unified interface for all data practitioners of various coding skills to simplify analytics workflows from data ingestion and preparation to data exploration and visualization to ML model creation and use. It also allows you to use simple SQL to access Vertex AI foundational models directly inside BigQuery for text processing tasks, such as sentiment analysis, entity extraction, and many more without having to deal with specialized models.
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rdi-exchange-prototype
Rights Exchange prototype from the Rights Data Integration project
Implementation in Java of a prototypical Rights Exchange as defined in the standards of the Linked Content Coalition (http://linkedcontentcoalition.org) and the Rights Data Integration project (http://www.rdi-project.org). Shows how to parse CRF-XML data containing Creation, Rights, RightsOffer, and Party data, to pose and respond to queries of a Hub, and to convert CRF-XML data into HTML for display. -
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The Dynamic Ordinal Classification (DOC) Toolbox contains different sequence classification methods including Conditional Ordinal Random Fields (CORF), Hidden Conditional Ordinal Random Fields (HCORF), Conditional Random Fields (CRF) , Hidden Conditional Random Fields (HCRF) and Variable State Latent Conditional Random Fields (VSL-CRF).
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Drug Extraction
Drug name extraction
Drug name recognition and normalisation/grounding to DrugBank ids and standard names. Package provides 2 taggers: 1. DrugTagger - CRF-based with DrugBank presence feature (see feature set for details). 2. DrugnameGazetteer - gazetteer/dictionary-based. Dictionary created from DrugBank.ca database. Both taggers include grounding/normalisation to DrugBank ids and standard names. Feature set: Word, Word-1, Word+1, Word-1_Word, Word_Word+1, DrugBankPresence, POS DrugBankPresence feature... -
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C++, Matlab and Python library for Hidden-state Conditional Random Fields. Implements 3 algorithms: LDCRF, HCRF and CRF. For Windows and Linux, 32- and 64-bits. Optimized for multi-threading. Works with sparse or dense input features.
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ML Toolbox
Matlab toolbox for Machine Learning
Matlab toolbox designed to simplify training, validation and testing process for multiple probabilistic models, including SVM, HMM and CRF. The toolbox is designed to work with Matlab Distributed Engine, allowing a distributed training of the probabilistic models. -
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GeoSegmenter
A Chinese word segmenter for the geoscience domain
GeoSegmenter is a Chinese word segmenter built specifically for the geoscience domain. It uses the conditional random fields (CRF) framework to build segmentation models. GeoSegmenter is trained with manually annotated geoscience documents. -
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CRF Segmenter
An improved method for discriminating Chinese word segmenter
CRF Segmenter is an improved method for discriminating Chinese word segmenter. We introduce some global features and context features and get almost the same performance only with much smaller corpus. -
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CRFSharp
CRFSharp is a .NET(C#) implementation of Conditional Random Field
CRFSharp(aka CRF#) is a .NET(C#) implementation of Conditional Random Fields, an machine learning algorithm for learning from labeled sequences of examples. It is widely used in Natural Language Process (NLP) tasks, for example: word breaker, postagging, named entity recognized, query chunking and so on. CRF#'s mainly algorithm is the same as CRF++ written by Taku Kudo. It encodes model parameters by L-BFGS. Moreover, it has many significant improvement than CRF++, such as totally parallel... -
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CRF is a Java implementation of Conditional Random Fields, an algorithm for learning from labeled sequences of examples. It also includes an implementation of Maximum Entropy learning.
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WordSegment
wordseg project is a word segment module implemented by C#
wordseg project is a word segment module implemented by C#. It is used to segment text into tokens and to label token's attribute according its context and semantic by front-maximum matching and CRF algorithms. The following are some sentences need to be segmented: 张晓晨和付仲恺一起坐在家（西坝河东里社区）里的沙发上看非诚勿扰。 百度公司的名字源于“众里寻他千百度”这诗句。 After above sentences be segmented by wordseg, the result as follows for each sentence: 张晓晨[PER] 和 付仲恺[PER] 一起 坐 在 家 （ 西坝河东里社区[LOC] ） 里 的 沙发[PDT] 上 看 非 诚 勿扰 。 百度公司[ORG] 的 名字... -
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CRF decoder is the simplified version of CRF++, only for decoding the sequential data. It removes the training component and its correspondent codes from CRF++, which makes CRF decoder more reabable and understandable for freshman.
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Pocket CRF is a modified version of CRF++, it maintains the simplicity of CRF++ and is able to use high order features. Pocket M3N is a simple Max Margin Markov Networks package for sequence labeling tasks.
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The easy-to-read Java implementaion of conditional random fields written by ZHOU Yun. This project can be seen as the simplified Java version of the FlexCRFs. This project is based on the CRF package of Sunita Sarawagi and FlexCRFs of Xuan-Hieu Phan.
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CRF++ is a simple, customizable, and open source implementation of Conditional Random Fields (CRFs) for segmenting/labeling sequential data. CRF++ is designed for generic purpose and will be applied to a variety of NLP tasks.
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Conditional Random Field(CRF) is a probabilistic model used in labeling or parsing sequential data. We provide a COM wrapper for CrfPP,which makes it easier to use for clients implemented in different languaes like C#,VB,C++ and script languages.
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Conrad is both a high performance Conditional Random Field engine which can be applied to a variety of machine learning problems and a specific set of models for gene prediction using semi-Markov CRFs.