Search Results for "/storage/emulated/0/android/data/net.sourceforge.uiq3.fx603p/files" - Page 5

Showing 268 open source projects for "/storage/emulated/0/android/data/net.sourceforge.uiq3.fx603p/files"

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    Odoo Business Applications

    Odoo is a software suite to better manage and run your company.

    Odoo is a fully integrated, customizable, open-source software packed with hundreds of expertly designed business applications. Odoo’s intuitive database is able to meet a majority of business needs, such as: CRM, Sales, Project, Manufacturing, Inventory, and Accounting, just to name a few.
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    Unlike spreadsheets or clunky PSAs, Float offers a clear, centralized view to schedule teams, plan capacity, estimate work, and track margins in real-time so that you can keep your people and profits on track.
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  • 1
    TNN

    TNN

    Uniform deep learning inference framework for mobile

    TNN, a high-performance, lightweight neural network inference framework open sourced by Tencent Youtu Lab. It also has many outstanding advantages such as cross-platform, high performance, model compression, and code tailoring. The TNN framework further strengthens the support and performance optimization of mobile devices on the basis of the original Rapidnet and ncnn frameworks. At the same time, it refers to the high performance and good scalability characteristics of the industry's...
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  • 2
    YOLO ROS

    YOLO ROS

    YOLO ROS: Real-Time Object Detection for ROS

    ...In the following ROS package, you are able to use YOLO (V3) on GPU and CPU. The pre-trained model of the convolutional neural network is able to detect pre-trained classes including the data set from VOC and COCO, or you can also create a network with your own detection objects. The YOLO packages have been tested under ROS Noetic and Ubuntu 20.04. We also provide branches that work under ROS Melodic, ROS Foxy and ROS2. Darknet on the CPU is fast (approximately 1.5 seconds on an Intel Core i7-6700HQ CPU @ 2.60GHz × 8) but it's like 500 times faster on GPU! ...
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  • 3
    TerarkDB

    TerarkDB

    A RocksDB compatible KV storage engine with better performance

    TerarkDB is an open-source storage engine designed as a replacement for RocksDB — offering improved performance, better compression, and optimized tail-latency for key-value workloads. It aims to be drop-in compatible with existing RocksDB setups: you can migrate most RocksDB instances over to TerarkDB without rewriting your storage logic. Under the hood, TerarkDB employs advanced data structures and compression strategies to reduce I/O, memory usage, and latency variability — delivering higher throughput and more predictable performance under heavy load. ...
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  • 4
    wav2letter++

    wav2letter++

    Facebook AI research's automatic speech recognition toolkit

    ...After installing, run export KENLM_ROOT_DIR=... so that wav2letter++ can find it. This is needed because KenLM doesn't support a make install step.wav2letter++ expects audio and transcription data to be prepared in a specific format so that they can be read from the pipelines. Each dataset (test/valid/train) needs to be in a separate file with one sample per line. A sample is specified using 4 columns separated by space (or tabs).
    Downloads: 0 This Week
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    Multi-Entity Cloud Accounting Software for Growing Businesses

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  • 5
    Turi Create

    Turi Create

    Simplifies the development of custom machine learning models

    Turi Create simplifies the development of custom machine learning models. You don't have to be a machine learning expert to add recommendations, object detection, image classification, image similarity or activity classification to your app. If you want your app to recognize specific objects in images, you can build your own model with just a few lines of code. Turi Create supports macOS 10.12+, Linux (with glibc 2.10+), Windows 10 (via WSL). Turi Create requires Python 2.7, 3.5, 3.6, 3.7,...
    Downloads: 10 This Week
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  • 6
    Euler

    Euler

    A distributed graph deep learning framework.

    Data in the fields of text, speech, and images is easier to process into a grid-like type of Euclidean space, which is suitable for processing by existing deep learning models. Graph is a data type in non-Euclidean space and cannot be directly applied to existing methods, requiring a specially designed graph neural network system. Graph-based learning methods such as graph neural networks combine end-to-end learning with inductive reasoning, and are expected to solve a series of problems such as relational reasoning and interpretability that deep learning cannot handle.
    Downloads: 0 This Week
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  • 7
    SmartOpenCV

    SmartOpenCV

    OpenCV enhancement library for Android

    SmartOpenCV is an enhanced computer vision toolkit built on top of OpenCV that aims to simplify and extend common image processing and computer vision tasks through higher-level abstractions and utilities. It provides pre-built modules and optimized pipelines for tasks such as object detection, image transformation, and feature extraction, reducing the need for low-level implementation. The framework is designed to be more developer-friendly than raw OpenCV by offering cleaner APIs and...
    Downloads: 0 This Week
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  • 8
    fastText

    fastText

    Library for fast text classification and representation

    ...Nowadays, the dominant approach to build such classifiers is machine learning, that is learning classification rules from examples. In order to build such classifiers, we need labeled data, which consists of documents and their corresponding categories (or tags, or labels).
    Downloads: 3 This Week
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  • 9
    SINGA

    SINGA

    A distributed deep learning platform

    Apache SINGA is an Apache Top Level Project, focusing on distributed training of deep learning and machine learning models. Various example deep learning models are provided in SINGA repo on Github and on Google Colab. SINGA supports data parallel training across multiple GPUs (on a single node or across different nodes). SINGA supports various popular optimizers including stochastic gradient descent with momentum, Adam, RMSProp, and AdaGrad, etc. SINGA records the computation graph and applies the backward propagation automatically after forward propagation. The optimization of memory are implemented in the Device class. ...
    Downloads: 0 This Week
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    Centralized Workload Automation and Job Scheduling

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    Orchestrates any process from a single point of control. Build reliable, low-code workflows in half the time. Develop end-to-end business and IT processes faster with hundreds of drag-and-drop actions. Coordinate enterprise-wide MFT processes using dozens of prebuilt actions for common file operations.
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  • 10

    FastoCloud PRO

    IPTV/NVR/CCTV/Video cloud https://fastocloud.com

    IPTV/Video cloud Features: Cross-platform (Linux, MacOSX, FreeBSD, Raspbian/Armbian) GPU/CPU Encode/Decode/Post Processing Stream statistics CCTV Adaptive hls streams Load balancing Temporary urls HLS push EPG scanning Subtitles to text conversions AD insertion Logo overlay Video effects Relays Timeshifts Catchups Playlists Restream/Transcode from online streaming services like Youtube, Twitch ...
    Downloads: 0 This Week
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  • 11
    Speech Recognition in English & Polish

    Speech Recognition in English & Polish

    Speech recognition software for English & Polish languages

    ...SkryBot Administracyjny - for civil and government administration. 3. SkryBot Medycyna Rodzinna - for physicians Professional version of SkryBot (commercial) offers you: 1. Audio conversion and cutting sound files into smaller ones. 2. Searching for words or phrases in sound files (recognized by SkryBot). 3. Editing sound files and automatic cutting off long silence parts in audio file.
    Downloads: 4 This Week
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  • 12
    The Integrating Vision Toolkit (IVT) is a powerful and fast C++ computer vision library with an easy-to-use object-oriented architecture. It offers its own multi-platform GUI toolkit. OpenCV is integrated optionally. Website: http://ivt.sourceforge.net
    Downloads: 3 This Week
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  • 13

    Safe Harbor Deidentification

    Safe Harbor Deidentification for medical documents

    Phalanx - Deidentify Safe Harbor Deidentification Mode of Phalanx is an abridged pipeline of NLP annotators culminating in NER annotators which write output of text offsets. It uses the Safe Harbor deidentification method.
    Downloads: 0 This Week
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  • 14
    Electronic Circuit Optimization

    Electronic Circuit Optimization

    Optimer: a SPICE base electrical/ electronic circuit optimization tool

    This project is dedicated to the optimization of (any) electrical and electronic circuits and components using evolutionary and heuristic algorithms incorporated with SPICE simulators (such as HSPICE, ngSPICE, etc.). We provide Optimer, which is a user graphical interface for circuit design and optimization. Website: https://www.circuitoptimization.com/ E-mail: contact@circuitoptimization.com/
    Downloads: 1 This Week
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  • 15
    xLearn

    xLearn

    High performance, easy-to-use, and scalable machine learning (ML)

    xLearn is a high-performance, easy-to-use, and scalable machine learning package that contains linear model (LR), factorization machines (FM), and field-aware factorization machines (FFM), all of which can be used to solve large-scale machine learning problems. xLearn is especially useful for solving machine learning problems on large-scale sparse data. Many real-world datasets deal with high dimensional sparse feature vectors like a recommendation system where the number of categories and users is on the order of millions. In that case, if you are a user of liblinear, libfm, and libffm, now xLearn is another better choice.
    Downloads: 0 This Week
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  • 16
    The Mobility Open Architecture Simulation and Tools (MOAST) framework aids in the development of autonomous robots. It includes an architecture, control modules, interface specs, and data sets and is fully integrated with the USARSim simulation system.
    Downloads: 0 This Week
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  • 17
    Scalable Distributed Deep-RL

    Scalable Distributed Deep-RL

    A TensorFlow implementation of Scalable Distributed Deep-RL

    Scalable Agent is the open implementation of IMPALA (Importance Weighted Actor-Learner Architectures), a highly scalable distributed reinforcement learning framework developed by Google DeepMind. IMPALA introduced a new paradigm for efficiently training agents across large-scale environments by decoupling acting and learning processes. In this architecture, multiple actor processes interact with their environments in parallel to collect trajectories, which are then asynchronously sent to a...
    Downloads: 2 This Week
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  • 18
    Simd

    Simd

    High performance image processing library in C++

    ...The Simd Library has C API and also contains useful C++ classes and functions to facilitate access to C API. The library supports dynamic and static linking, 32-bit and 64-bit Windows, Android and Linux, MSVS, G++ and Clang compilers, MSVS project and CMake build systems.
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    Downloads: 58 This Week
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  • 19
    PyTom

    PyTom

    http://www.sciencedirect.com/science/article/pii/S1047847711003492

    PyTom is a toolbox developed for interpreting cryo electron tomography data. All steps from reconstruction, localization, alignment and classification are covered with standard and improved methods. Please sign up to our mailing list to keep up with the most recent updates and versions.
    Downloads: 1 This Week
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  • 20
    Convolutional Recurrent Neural Network

    Convolutional Recurrent Neural Network

    Convolutional Recurrent Neural Network (CRNN) for image-based sequence

    ...This hybrid approach allows the model to recognize sequences of characters directly from images without requiring explicit character segmentation. The implementation also integrates the Connectionist Temporal Classification (CTC) loss function, enabling end-to-end training of the model using labeled sequence data. CRNN has been widely used in computer vision tasks that require interpreting text embedded in images, such as reading street signs, documents, or natural scene text.
    Downloads: 0 This Week
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  • 21
    VideoMan Library

    VideoMan Library

    C++ library for image acquisition and visualization

    Library for capturing video from cameras, 3d sensors, frame-grabbers, video files and image sequences. It can also display multiple images using OpenGL with different layouts. Easy integration with OpenCV, CUDA... Perfect for computer vision. Keywords: video capture, computer vision, machine vision, opencv, opengl, cameras, video input devices, firewire, usb, gige
    Downloads: 0 This Week
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  • 22
    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: 4 This Week
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  • 23
    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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  • 24
    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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  • 25
    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. ...
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