Search Results for "/storage/emulated/0/android/data/net.sourceforge.uiq3.fx603p/files" - Page 83

Showing 2752 open source projects for "/storage/emulated/0/android/data/net.sourceforge.uiq3.fx603p/files"

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  • 1

    PanoramaServer

    Open Source Panorama Server for free virtual tour of 360 degrees views

    Ideal for creating virtual tours of panoramic views for all sorts including property exhibition for brokers at real estate agencies/property agents, tour guide for indoor/outdoor venues, information to public/private facilities for curators, travel journal for tourist as log book, backdrop setting for storytelling, treasure hunt like games, big data mining for pattern through computer vision in artificial intelligence, etc. It is like creating your own Google Map Street View. All is required by the user is to have photos of equirectangular format (panorama) taken from 3D cameras common for on-site premises. These images can be referenced by the PanoramaServer to create virtual travels with 360 degrees view where viewers can navigate to different locations, view information, etc. ...
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  • 2
    insofts player
    insofts-player Free media player, with which you can easily and conveniently view video and listen to audio files in various formats, without installing additional codecs. View streaming video, audio.   Constantly updating the online media library Additional features: sound recording, uart protocol support, speech to text
    Downloads: 0 This Week
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  • 3
    Siamese and triplet learning

    Siamese and triplet learning

    Siamese and triplet networks with online triplet mining in PyTorch

    ...The repository demonstrates how to train these models using contrastive loss and triplet loss functions, which encourage embeddings of similar samples to be close while pushing dissimilar samples farther apart. It includes data loaders, training scripts, neural network architectures, and evaluation metrics that allow researchers to experiment with different embedding learning strategies. The project also implements online pair and triplet mining techniques to efficiently generate training examples during model training.
    Downloads: 0 This Week
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  • 4
    JuliusModels

    JuliusModels

    Open source speech models for Julius in English and other languages.

    ...Its aim is to give access a wider community of speech recognition enthusiasts to quality models, which they can use in their own projects on different OS platforms (Unix, Windows, etc...) All of the models are based on HTK modelling software and data sets available freely on the Internet.
    Downloads: 7 This Week
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  • 5
    Serenata de Amor

    Serenata de Amor

    Artificial Intelligence for social control of public administration

    ...Machine learning techniques and data analysis pipelines are used to identify anomalies that may indicate misuse of public funds. The system also includes automated tools that assist in processing large datasets and generating reports about potentially problematic transactions. By making both the data and the analysis tools open source, the project encourages civic participation and collaborative oversight of government activities.
    Downloads: 0 This Week
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  • 6
    voice-elements

    voice-elements

    Web Component wrapper to the Web Speech API

    ...Instead of manually dealing with JavaScript APIs like SpeechSynthesis and SpeechRecognition, developers can drop custom elements such as <voice-player> and <voice-recognition> into their markup and configure them with attributes. Built originally with Polymer, it follows the early Web Components ecosystem patterns, integrating custom elements, templates, and data binding. The project includes demos that show how to autoplay spoken text or start listening for voice commands when the element loads, helping developers quickly grasp usage. Because it is based on the browser’s native Web Speech API, it does not require external services, although support can vary across browsers. voice-elements is particularly handy for prototypes, educational projects, and small apps.
    Downloads: 3 This Week
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  • 7

    DGRLVQ

    Dynamic Generalized Relevance Learning Vector Quantization

    Some of the usual problems for Learning vector quantization (LVQ) based methods are that one cannot optimally guess about the number of prototypes required for initialization for multimodal data structures i.e.these algorithms are very sensitive to initialization of prototypes and one has to pre define the optimal number of prototypes before running the algorithm. If a prototype, for some reasons, is ‘outside’ the cluster which it should represent and if there are points of a different categories in between, then the other points act as a barrier and the prototype will not find its optimum position during training. ...
    Downloads: 0 This Week
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  • 8
    Edward

    Edward

    A probabilistic programming language in TensorFlow

    ...Edward is a Python library for probabilistic modeling, inference, and criticism. It is a testbed for fast experimentation and research with probabilistic models, ranging from classical hierarchical models on small data sets to complex deep probabilistic models on large data sets. Edward fuses three fields, Bayesian statistics and machine learning, deep learning, and probabilistic programming. Edward is built on TensorFlow. It enables features such as computational graphs, distributed training, CPU/GPU integration, automatic differentiation, and visualization with TensorBoard. ...
    Downloads: 0 This Week
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  • 9
    TorchCraft

    TorchCraft

    Connecting Torch to StarCraft

    ...This white paper argues for using RTS games as a benchmark for AI research, and describes the design and components of TorchCraft. TorchCraft is a BWAPI module that sends StarCraft data out over a ZMQ connection. This lets you parse StarCraft data and interact with BWAPI from anywhere. The TorchCraft client should be installed from C++, Python, or Lua. We provide off-the-shelf solutions for Python and Lua.
    Downloads: 0 This Week
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  • 10
    Image classification models for Keras

    Image classification models for Keras

    Keras code and weights files for popular deep learning models

    All architectures are compatible with both TensorFlow and Theano, and upon instantiation the models will be built according to the image dimension ordering set in your Keras configuration file at ~/.keras/keras.json. For instance, if you have set image_dim_ordering=tf, then any model loaded from this repository will get built according to the TensorFlow dimension ordering convention, "Width-Height-Depth". Pre-trained weights can be automatically loaded upon instantiation (weights='imagenet'...
    Downloads: 2 This Week
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  • 11

    PyAIMLng

    The Next Generation of Python AIML Interpreter

    A Python AIML interpreter with non-compliant extensions. PyAIMLng is an interpreter for AIML (the Artificial Intelligence Markup Language), forked from Cort Stratton's PyAIML. PyAIMLng adds additional features which are not part of the AIML 1.0.1 specification in order to provide the bot master with a rich set of tools from which to build a more believable AIML bot.
    Downloads: 0 This Week
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  • 12
    Telegram::Bot

    Telegram::Bot

    Ruby gem for building Telegram Bot with optional Rails integration

    Tools for developing Telegram bots. Best used with Rails, but can be used in a standalone app. Supposed to be used in webhook mode in production, and poller mode in development, but you can use poller in production if you want.
    Downloads: 0 This Week
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  • 13
    DarkForestGo

    DarkForestGo

    DarkForest, the Facebook Go engine

    darkforestGo is an early deep-reinforcement-learning Go engine that combined a convolutional policy/value network with Monte Carlo Tree Search (MCTS) to play the full 19×19 game at a strong amateur level. The system couples fast GPU policy inference with CPU or GPU-assisted tree search so priors from the network guide exploration while search refines local tactics. Training pipelines mix supervised learning from human professional games and self-play fine-tuning, allowing the model to learn...
    Downloads: 0 This Week
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  • 14
    Tangent

    Tangent

    Source-to-source debuggable derivatives in pure Python

    Existing libraries implement automatic differentiation by tracing a program's execution (at runtime, like PyTorch) or by staging out a dynamic data-flow graph and then differentiating the graph (ahead-of-time, like TensorFlow). In contrast, Tangent performs ahead-of-time autodiff on the Python source code itself, and produces Python source code as its output. Tangent fills a unique location in the space of machine learning tools. As a result, you can finally read your automatic derivative code just like the rest of your program. ...
    Downloads: 0 This Week
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  • 15
    WikiSQL

    WikiSQL

    A large annotated semantic parsing corpus for developing NL interfaces

    A large crowd-sourced dataset for developing natural language interfaces for relational databases. WikiSQL is the dataset released along with our work Seq2SQL: Generating Structured Queries from Natural Language using Reinforcement Learning. Regarding tokenization and Stanza, when WikiSQL was written 3-years ago, it relied on Stanza, a CoreNLP python wrapper that has since been deprecated. If you'd still like to use the tokenizer, please use the docker image. We do not anticipate switching...
    Downloads: 1 This Week
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  • 16
    Seldon Server

    Seldon Server

    Machine learning platform and recommendation engine on Kubernetes

    ...Seldon Core is a progression of the goals of the Seldon-Server project but also a more restricted focus to solving the final step in a machine learning project which is serving models in production. Seldon Server is a machine learning platform that helps your data science team deploy models into production. It provides an open-source data science stack that runs within a Kubernetes Cluster. You can use Seldon to deploy machine learning and deep learning models into production on-premise or in the cloud (e.g. GCP, AWS, Azure).
    Downloads: 0 This Week
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  • 17
    AI learning

    AI learning

    AiLearning, data analysis plus machine learning practice

    We actively respond to the Research Open Source Initiative (DOCX) . Open source today is not just open source, but datasets, models, tutorials, and experimental records. We are also exploring other categories of open source solutions and protocols. I hope you will understand this initiative, combine this initiative with your own interests, and do what you can. Everyone's tiny contributions, together, are the entire open source ecosystem. We are iBooker, a large open-source community,...
    Downloads: 0 This Week
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  • 18
    Command Line Parser GetPot

    Command Line Parser GetPot

    Tool to parse the command line and configuration files.

    Powerful command line and configuration file parsing for C++, Python, Ruby and Java (others to come). This tool provides many features, such as separate treatment for options, variables, and flags, unrecognized object detection, prefixes and much more.
    Downloads: 1 This Week
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  • 19
    Subtitle Workshop

    Subtitle Workshop

    Free subtitle editor

    Subtitle Workshop is a free application for creating, editing, and converting text-based subtitle files. It supports all the subtitle formats you need and has all the features you would want.
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    Downloads: 1,317 This Week
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  • 20
    Al-Mintiq: Arabic eSpeak

    Al-Mintiq: Arabic eSpeak

    Arabic voice files for eSpeak system

    Arabic files and voices for eSpeak Text to speech system, المنطيق : ملفات اللغة العربية لبرنامج توليد الكلام من النص إسبيك
    Downloads: 3 This Week
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  • 21
    The Edge Machine Learning library

    The Edge Machine Learning library

    Machine learning algorithms for edge devices

    Machine learning models for edge devices need to have a small footprint in terms of storage, prediction latency, and energy. One instance of where such models are desirable is resource-scarce devices and sensors in the Internet of Things (IoT) setting. Making real-time predictions locally on IoT devices without connecting to the cloud requires models that fit in a few kilobytes.These algorithms can train models for classical supervised learning problems with memory requirements that are orders of magnitude lower than other modern ML algorithms. ...
    Downloads: 0 This Week
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  • 22
    GNAT

    GNAT

    GNAT recognizes gene names in text and maps them to NCBI Entrez Gene

    ...It will detect mentions of genes in text, such as PubMed/Medline abstracts, and disambiguate them to remove false positives and map them to the correct entry in the NCBI Entrez Gene database by gene ID. March 2017: We started to upload GNAT output on Medline. See files/results/medline/.
    Downloads: 1 This Week
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  • 23
    auto_ml

    auto_ml

    Automated machine learning for analytics & production

    ...Here's an example that includes serializing and loading the trained model, then getting predictions on single dictionaries, roughly the process you'd likely follow to deploy the trained model. Before you go any further, try running the code. Load up some data (either a DataFrame, or a list of dictionaries, where each dictionary is a row of data). Make a column_descriptions dictionary that tells us which attribute name in each row represents the value we’re trying to predict. Pass all that into auto_ml, and see what happens! You can pass in your own function to perform feature engineering on the data.
    Downloads: 0 This Week
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  • 24
    FM2TXT

    FM2TXT

    RtlSdr listen to radio, recognize audio, and writes text file log

    Just log your favorite FM station speech to a text file using rtl-sdr dongle and speech recognition. Cross-platform tool. Follow the README on the download page for Windows installation. https://sourceforge.net/projects/fm2txt-rtlsdr/files/ If you prefer GitHub source, not SF: https://github.com/randaller/fm2txt For those, who want to recognize from soundcard, not from rtl-sdr (this allows to transcribe NFM etc): https://github.com/randaller/souncard2txt
    Downloads: 0 This Week
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  • 25

    SW-DLP: Developing ontoLogy by Profiling

    a tool for easing the ontologies editing and evolution (Semantic Web)

    The DLP tool was ideated and developed by: Dr. Luca Mazzola, MsC. Patrick Kapahnke, and PD Dr. Matthias Klusch at the German Research Center for Artificial Intelligence DFKI GmbH (http://www.dfki.de ) in Saarbrücken, Germany. Copyright: DFKI, 2017, licence GLP see https://www.gnu.org/licenses/gpl-3.0.en.html For bug reports, technical problems and feature requests please contact: Luca Mazzola: luca.mazzola@dfki.de or mazzola.luca@gmail.com Patrick Kapahnke: patrick.kapahnke@dfki.de
    Downloads: 0 This Week
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