Search Results for "git:/git.code.sf.net/p/docfetcher/code" - Page 54

Showing 1622 open source projects for "git:/git.code.sf.net/p/docfetcher/code"

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  • Dominate AI Search Results Icon
    Dominate AI Search Results

    Generative Al is shaping brand discovery. AthenaHQ ensures your brand leads the conversation.

    AthenaHQ is a cutting-edge platform for Generative Engine Optimization (GEO), designed to help brands optimize their visibility and performance across AI-driven search platforms like ChatGPT, Google AI, and more.
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  • The top-rated AI recruiting platform for faster, smarter hiring. Icon
    The top-rated AI recruiting platform for faster, smarter hiring.

    Humanly is an AI recruiting platform that automates candidate conversations, screening, and scheduling.

    Humanly is an AI-first recruiting platform that helps talent teams hire in days, not months—without adding headcount. Our intuitive CRM pairs with powerful agentic AI to engage and screen every candidate instantly, surfacing top talent fast. Built on insights from over 4 million candidate interactions, Humanly delivers speed, structure, and consistency at scale—engaging 100% of interested candidates and driving pipeline growth through targeted outreach and smart re-engagement. We integrate seamlessly with all major ATSs to reduce manual work, improve data flow, and enhance recruiter efficiency and candidate experience. Independent audits ensure our AI remains fair and bias-free, so you can hire confidently.
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  • 1
    php-text-generator

    php-text-generator

    Fast SEO text generator on a mask

    ...Easy wrapping thanks to the integrated interface. Covered tests. Written by PSR standards and 100% covered with documentation (PHP-Doc) Without external dependencies. The code is checked by the static analyzer PhpStan lvl 7.
    Downloads: 0 This Week
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  • 2
    Learn_Machine_Learning_in_3_Months

    Learn_Machine_Learning_in_3_Months

    This is the code for "Learn Machine Learning in 3 Months"

    This repository outlines an ambitious self-study curriculum for learning machine learning in roughly three months, emphasizing breadth, momentum, and hands-on practice. It sequences core topics—math foundations, classic ML, deep learning, and applied projects—so learners can pace themselves week by week. The plan mixes reading, lectures, coding assignments, and small build-it-yourself projects to reinforce understanding through repetition and implementation. Because ML is a wide field, the...
    Downloads: 0 This Week
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  • 3
    CFNet

    CFNet

    Training a Correlation Filter end-to-end allows lightweight networks

    ...This allows the tracker to be both computationally efficient and robust to appearance changes such as scale, rotation, and illumination variations. The repository provides pre-trained models, training code, and testing scripts for evaluating the tracker on standard benchmarks. By bridging the gap between correlation filters and deep learning, CFNet provides a foundation for further research in real-time object tracking.
    Downloads: 1 This Week
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  • 4
    ...Obtaining the teachingbox: FOR USERS: If you want to download the latest releases, please visit: http://search.maven.org/#search|ga|1|teachingbox FOR DEVELOPERS: 1) If you use Apache Maven, just add the following dependency to your pom.xml: <dependency> <groupId>org.sf.teachingbox</groupId> <artifactId>teachingbox-core</artifactId> <version>1.2.3</version> </dependency> 2) If you want to check out the most recent source-code: git clone https://git.code.sf.net/p/teachingbox/core teachingbox-core Documentation: https://sourceforge.net/p/teachingbox/documentation/HEAD/tree/trunk/manual/
    Downloads: 0 This Week
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  • BrandMail Email Signatures for Outlook Icon
    BrandMail Email Signatures for Outlook

    Leverage every email as an opportunity to brand consistently and minimise the security risks associated with the tampering of HTML signatures.

    BrandMail®, developed by BrandQuantum, is a software solution that seamlessly integrates with Microsoft Outlook to empower every employee in the organisation to automatically create consistently branded emails via a single toolbar that provides access to brand standards and the latest pre-approved content.
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  • 5
    MatlabFunc

    MatlabFunc

    Matlab codes for feature learning

    ...These functions cover areas such as matrix operations, optimization, data processing, and visualization, making them broadly applicable across different research domains. The project is intended to provide reusable and adaptable MATLAB code that can save time for researchers and students working on experimental or applied projects. By consolidating these tools in one place, MatlabFunc serves as a practical reference and toolkit for both academic and engineering purposes. Contributions and improvements from the community are encouraged, allowing the repository to grow into a richer resource over time.
    Downloads: 1 This Week
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  • 6
    Deep Reinforcement Learning TensorFlow

    Deep Reinforcement Learning TensorFlow

    TensorFlow implementation of Deep Reinforcement Learning papers

    Deep Reinforcement Learning TensorFlow is a comprehensive TensorFlow codebase that implements several foundational deep reinforcement learning algorithms for educational and experimental use. The repository focuses on clarity and modularity so users can study how different RL approaches are built and compare their behavior across environments. It includes implementations of well-known algorithms such as Deep Q-Networks (DQN), policy gradients, and related variants, demonstrating how neural...
    Downloads: 0 This Week
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  • 7
    SSD Keras

    SSD Keras

    A Keras port of single shot MultiBox detector

    ...The main goal of this project is to create an SSD implementation that is well documented for those who are interested in a low-level understanding of the model. The provided tutorials, documentation and detailed comments hopefully make it a bit easier to dig into the code and adapt or build upon the model than with most other implementations out there (Keras or otherwise) that provide little to no documentation and comments. Use one of the provided trained models for transfer learning.
    Downloads: 0 This Week
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  • 8
    stanford-tensorflow-tutorials

    stanford-tensorflow-tutorials

    This repository contains code examples for the Stanford's course

    This repository contains code examples for the course CS 20: TensorFlow for Deep Learning Research. It will be updated as the class progresses. Detailed syllabus and lecture notes can be found in the site. For this course, I use python3.6 and TensorFlow 1.4.1.
    Downloads: 0 This Week
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  • 9
    EvalAI

    EvalAI

    Evaluating state of the art in AI

    ...If the challenge needs extra computational power, challenge organizers can easily add their own cluster of worker nodes to process participant submissions while we take care of hosting the challenge, handling user submissions, and maintaining the leaderboard. EvalAI lets participants submit code for their agent in the form of docker images which are evaluated against test environments on the evaluation server. During the evaluation, the worker fetches the image, test environment, and model snapshot and spins up a new container to perform the evaluation.
    Downloads: 0 This Week
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  • The Apple Device Management and Security Platform Icon
    The Apple Device Management and Security Platform

    For IT teams at organizations that run on Apple

    Achieve harmony across your Apple device fleet with Kandji's unmatched management and security capabilities.
    Learn More
  • 10
    mAP

    mAP

    Evaluates the performance of your neural net for object recognition

    In practice, a higher mAP value indicates a better performance of your neural net, given your ground truth and set of classes. The performance of your neural net will be judged using the mAP criteria defined in the PASCAL VOC 2012 competition. We simply adapted the official Matlab code into Python (in our tests they both give the same results). First, your neural net detection-results are sorted by decreasing confidence and are assigned to ground-truth objects. We have "a match" when they share the same label and an IoU >= 0.5 (Intersection over Union greater than 50%). This "match" is considered a true positive if that ground-truth object has not been already used (to avoid multiple detections of the same object).
    Downloads: 0 This Week
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  • 11
    NOMAD is a C++ code that implements the MADS algorithm (Mesh Adaptive Direct Search) for difficult blackbox optimization problems. Such problems occur when the functions to optimize are costly computer simulations with no derivatives.
    Downloads: 0 This Week
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  • 12
    PyTorch Book

    PyTorch Book

    PyTorch tutorials and fun projects including neural talk

    This is the corresponding code for the book "The Deep Learning Framework PyTorch: Getting Started and Practical", but it can also be used as a standalone PyTorch Getting Started Guide and Tutorial. The current version of the code is based on pytorch 1.0.1, if you want to use an older version please git checkout v0.4or git checkout v0.3. Legacy code has better python2/python3 compatibility, CPU/GPU compatibility test.
    Downloads: 0 This Week
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  • 13
    The Deep Review

    The Deep Review

    A collaboratively written review paper on deep learning, genomics, etc

    ...New contributors are welcome and will be listed as version 2.0 authors. Manubot is a system for writing scholarly manuscripts via GitHub. Manubot automates citations and references, versions manuscripts using git, and enables collaborative writing via GitHub.
    Downloads: 0 This Week
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  • 14
    Detect and Track

    Detect and Track

    Code release for "Detect to Track and Track to Detect", ICCV 2017

    ...The framework unifies object detection and tracking into a single pipeline, allowing detection to support tracking and tracking to enhance detection performance. Built upon a modified version of R-FCN, the code provides implementations using backbone networks such as ResNet-50, ResNet-101, ResNeXt-101, and Inception-v4, with results demonstrating state-of-the-art accuracy on the ImageNet VID dataset. The repository includes MATLAB-based training and testing scripts, along with pre-trained models and pre-computed region proposals for reproducibility. ...
    Downloads: 2 This Week
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  • 15

    IGVC IITK Data

    Data useful for testing autonomous navigation algorithms

    This repository is only used for the purpose of dataset storage for Team IGVC, IITK. For the relevant code, see our GitHub repositories. (https://github.com/igvc-iitk). The recorded data is used for testing various algorithms related to Computer Vision, SLAM, Motion Planning etc.
    Downloads: 0 This Week
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  • 16
    Image classification models for Keras

    Image classification models for Keras

    Keras code and weights files for popular deep learning models

    ...Pre-trained weights can be automatically loaded upon instantiation (weights='imagenet' argument in model constructor for all image models, weights='msd' for the music tagging model). Weights are automatically downloaded if necessary, and cached locally in ~/.keras/models/. This repository contains code for the following Keras models, VGG16, VGG19, ResNet50, Inception v3, and CRNN for music tagging.
    Downloads: 1 This Week
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  • 17

    Accord.Net Face Detection Recognition

    Accord.Net Face Detection Recognition

    The most simplest clean hard core code for Accord.Net Face Detection with Face Cropping in Cs Vb for **** FACE RECOGNITION **** using Accord.Net like the first screenshot contact dbinxecod@gmail.com Full source code ahead for face recognition using Accort.Net Donate for $108 then you'll get the full source code! Please see screen shot of face recognition via Accord.NET
    Downloads: 0 This Week
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  • 18

    ANGie

    Alice Next Generation (internet entity)

    An AIML based chat bot building on the original Alice AIML 1.0.1 set produced by Dr. Wallace and the ALICE AI Foundation and the PyAIML code base written by Cort Stratton, the ANGie project incorporates additional AIML sets, adds its own AIML to the set, adds new AIML tags and additional code to provide more dynamic responses and more logical case-based-reasoning. Reading through most AIML sets it seems like the authors' intention was to have a response to every input that a bot has ever seen. ...
    Downloads: 1 This Week
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  • 19

    PyGOAPng

    Python Goal Oriented Action Planning (GOAP) library

    A library for implementing GOAP in an AI agent. Based on pygoap v3 by Leif Theden et al. Updated code to work without having pygame installed, bug-fixed functions to make them implement the behaviors that were expected, and implemented desired behaviors so that the Pirate demo works properly for all known actions and goals.
    Downloads: 0 This Week
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  • 20
    Intel neon

    Intel neon

    Intel® Nervana™ reference deep learning framework

    neon is Intel's reference deep learning framework committed to best performance on all hardware. Designed for ease of use and extensibility. See the new features in our latest release. We want to highlight that neon v2.0.0+ has been optimized for much better performance on CPUs by enabling Intel Math Kernel Library (MKL). The DNN (Deep Neural Networks) component of MKL that is used by neon is provided free of charge and downloaded automatically as part of the neon installation. The gpu...
    Downloads: 0 This Week
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  • 21
    kcws

    kcws

    Deep Learning Chinese Word Segment

    ...Change to the code directory.After installing tensorflow, switch to the kcws code directory. Currently, the custom dictionary is supported in the decoding stage. Please refer to kcws/cc/test_seg.cc for specific usage. The dictionary is in text format.
    Downloads: 0 This Week
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  • 22
    Portable Robotics Eye Vergence Control

    Portable Robotics Eye Vergence Control

    Eye movements control portable on different robotic stereo heads

    ...The project allows a robust control and adaptive binocular coordination for different robot stereo platforms. Reference publications: Gibaldi, A., Vanegas, M., Canessa, A., & Sabatini, S. P. (2017). A portable bio-inspired architecture for efficient robotic vergence control. International Journal of Computer Vision,. Gibaldi, A., Canessa, A., Chessa, M., Sabatini, S. P., & Solari, F. (2011, October). A neuromorphic control module for real-time vergence eye movements on the iCub robot head. In Humanoid Robots (Humanoids), 2011
    Downloads: 0 This Week
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  • 23
    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. Tangent is useful to researchers and students who not only want to write their models in Python, but also read and debug automatically-generated derivative code without sacrificing speed and flexibility. ...
    Downloads: 0 This Week
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  • 24
    C++ Fuzzy Logic Programming Library - For problem solving in the fuzzy logic domain. It has an object oriented API well suited to C++ syntax for direct inclusion in source code. Portable to platforms that support the C++ STL.
    Downloads: 0 This Week
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  • 25
    Five video classification methods

    Five video classification methods

    Code that accompanies my blog post outlining five video classification

    Classifying video presents unique challenges for machine learning models. As I’ve covered in my previous posts, video has the added (and interesting) property of temporal features in addition to the spatial features present in 2D images. While this additional information provides us more to work with, it also requires different network architectures and, often, adds larger memory and computational demands.We won’t use any optical flow images. This reduces model complexity, training time, and...
    Downloads: 0 This Week
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