Search Results for "viterbi"
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Showing 12 open source projects for "viterbi"
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Get full visibility and control over your tasks and projects with Wrike.Wrike offers world-class features that empower cross-functional, distributed, or growing teams take their projects from the initial request stage all the way to tracking work progress and reporting results.
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The AI-powered unified PSA-RMM platform for modern MSPs.SuperOps.ai is the only PSA-RMM platform powered by intelligent automation and thoughtfully crafted for the new-age MSP. The platform also helps MSPs manage their projects, clients, and IT documents from a single place.
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gse
Go efficient multilingual NLP and text segmentation
...Support user and embed dictionary, Part-of-speech/POS tagging, analyze segment info, stop and trim words. Support multilingual: English, Chinese, Japanese and others. Support Traditional Chinese. Support HMM cut text use Viterbi algorithm. Support NLP by TensorFlow (in work). Named Entity Recognition (in work). Supports with elastic search and bleve. run JSON RPC service. -
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HMMBase.jl
Hidden Markov Models for Julia
HMMBase is not maintained anymore. It will keep being available as a Julia package but we encourage existing and new users to migrate to HiddenMarkovModels.jl which offers a similar interface. For more information see HiddenMarkovModels.jl: when did HMMs get so fast?. HMMBase provides a lightweight and efficient abstraction for hidden Markov models in Julia. Most HMMs libraries only support discrete (e.g. categorical) or Normal distributions. In contrast HMMBase builds upon Distributions.jl... -
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FRETtranslator
Translate smFRET trajectories into RNA secondary strucutures
FRETtranslator is a frame work that allows you to predict a sequence of RNA seondary structure transitions for a given smFRET trajectory. At its core it uses Viterbi-decoding. FRETtranslator combines smFRET data with RNA secondary structure predictions and RNA 3D structure sampling. As such it relies on input from additional software for RNA secondary structure and 3D structure predictions. -
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HMM-FRAME
Frameshift detection and correction for next-generation sequences
HMM-FRAME is designed to accurately locate and correct frameshift errors in next-generation sequencing (NGS) data using an augmented Viterbi algorithm on profile hidden Markov models (profile HMMs). By correcting the frameshift errors, it can classify more NGS sequences into their native protein domain families. -
Data management solutions for confident marketingVerify, deduplicate, manipulate, and assign records automatically to keep your CRM data accurate, complete, and ready for business.
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segment
Solve the Viterbi algorithm in a data stream
It is often necessary to assign a series of discrete values to continuosly variable data sequenced by time, position, etc., thereby parsing the data into fewer and larger segments of variable width. The 'segment' utility takes an input data stream as a Hidden Markov Model and applies the Viterbi algorithm to find the most likely segmentation path through the data. -
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SRM2 Sound Recognizer Mobile 2
A Sound Recognition Framework developed to J2ME plataform
...It has the following characteristics: - DTW - HMM (Discrete Models) - Suports Sound in PCM - Vector quantization using the k-means algorithm - Uses the algorithm Forward - Uses the algorithm Backward - Uses the Viterbi algorithm - Uses the Baum-Welch algorithm for training - Has features import and export data Further information is on Gaita 2012. -
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JaCHMM
Java Conditioned Hidden Markov Model library
The JaCHMM - the Java Conditioned Hidden Markov Model library - is a complete implementation of a CHMM in Java ready to use either on command line or as a module. The JaCHMM is licenced under the BSD licence. It gives an implementation of the Viterbi, Forward-Backward, Baum-Welch and K-Means algorithms, all adapted for the CHMM. JaCHMM is based on the JaHMM and also designed to achieve reasonable performance without making the code unreadable. Consequently, it offers a good way of applying the Conditioned Hidden Markov Model in various tasks, e.g., for scientific or teaching purposes. -
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CvHMM
Discrete Hidden Markov Models based on OpenCV
This project (CvHMM) is an implementation of discrete Hidden Markov Models (HMM) based on OpenCV. It is simple to understand and simple to use. The Zip file contains one header for the implementation and one main.cpp file for a demonstration of how it works. Hope it becomes useful for your projects. -
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Trofast Stavekontrol
Trofast is an intelligent spell checker.
Trofast is an intelligent spell checker library based on statistical analysis developed for the Danish language. It makes use of n-grams, hidden Markov models and the Viterbi-algorithm. -
The AI workplace management platformBy combining AI workflows, predictive intelligence, and automated insights, OfficeSpace gives leaders a complete view of how their spaces are used and how people work. Facilities, IT, HR, and Real Estate teams use OfficeSpace to optimize space utilization, enhance employee experience, and reduce portfolio costs with precision.
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Viterbi Decoder on the Cell Broadband Engine that reduces computational time and space complexity utilising the multi-core environment and thus improving its performance as compared to on single core architectures.
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This is a Viterbi HDL Code Generator (VHCG). It can generate the Verilog HDL codes of some kind of Viterbi Decoder which is scalable and parameterized. In-place-state-metric-storage is used in these decoders. I purpose that it can reduce repeated works i
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HmmSDK is a hidden Markov model (HMM) software development kit written in Java. It consists of core library of HMM functions (Forward-backward, Viterbi, and Baum-Welch algorithms) and toolkits for application development.
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