Search Results for "git:/git.code.sf.net/p/docfetcher/code" - Page 54
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Showing 1619 open source projects for "git:/git.code.sf.net/p/docfetcher/code"
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Outplacement, Executive Coaching and Career Development | CareermindsBy helping to avoid the potential risks of RIFs or layoffs through our global outplacement services, companies can move forward with their goals while preserving their internal culture, employer brand, and bottom lines.
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Fully managed relational database service for MySQL, PostgreSQL, and SQL ServerCloud SQL manages your databases so you don't have to, so your business can run without disruption. It automates all your backups, replication, patches, encryption, and storage capacity increases to give your applications the reliability, scalability, and security they need.
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Delphi Face Detection
Delphi face detection
...Runs on Windows XP to Windows 10 Available on MsAcceSS or SQLite Dataface! Depending on Request! You can reprogram / setup / configure / scale the Face Recognition accuracy! C++Builder Face Detection: FREE Source code! https://sourceforge.net/projects/cbuilder-opencv-face-detection/ C++Builder Face Recognition: https://sourceforge.net/projects/c-builder-face-recognition/ Technical Support is always online, thank you -
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Skater
Python library for model interpretation/explanations
...Model interpretation is the ability to explain and validate the decisions of a predictive model to enable fairness, accountability, and transparency in algorithmic decision-making. The library has embraced object-oriented and functional programming paradigms as deemed necessary to provide scalability and concurrency while keeping code brevity in mind. -
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Learn_Deep_Learning_in_6_Weeks
This is the Curriculum for "Learn Deep Learning in 6 Weeks"
...It begins with neural network fundamentals and moves through convolutional and recurrent architectures, optimization strategies, regularization, and transfer learning. The materials emphasize code-first understanding: building small models, training them on accessible datasets, and analyzing their behavior. Each week culminates in a tangible outcome—such as a working classifier or sequence model—so progress is visible and motivating. The plan also introduces practical considerations like GPU usage, checkpoints, and debugging training dynamics. ... -
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Generative Models
Collection of generative models, e.g. GAN, VAE in Pytorch
This project is a comprehensive open-source collection of implementations of various generative machine learning models designed to help researchers and developers experiment with deep generative techniques. The repository contains practical implementations of well-known architectures such as Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), Restricted Boltzmann Machines, and Helmholtz Machines, implemented primarily using modern deep learning frameworks like PyTorch... -
Ecwid is a hosted cloud commerce platform used by over 1.5 million merchants and offers the easiest way to add an online store to any website, social site or multiple sites simultaneously.Set up your Ecwid store once to easily sync and sell across a website, social media, marketplaces like Amazon, and live in-person. Get started with one, or try them all.
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LearningToCompare_FSL
Learning to Compare: Relation Network for Few-Shot Learning
...The core idea implemented here is the relation network, which learns to compare pairs of feature embeddings and output relation scores that indicate whether two images belong to the same class, enabling classification from only a handful of labeled examples. The repository provides training and evaluation code for standard few-shot benchmarks such as miniImageNet and Omniglot, making it possible to reproduce the experimental results reported in the paper. It includes model definitions, data loading logic, episodic training loops, and scripts that implement the N-way K-shot evaluation protocol common in few-shot research. Researchers can use this codebase as a starting point to test new ideas, modify relation modules, or transfer the approach to new datasets. -
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The source code has been migrated and is now hosted on Github: https://github.com/jenetics/jenetics Jenetics is an advanced Genetic Algorithm, Evolutionary Algorithm and Genetic Programming library, respectively, written in modern day Java. It is designed with a clear separation of the several algorithm concepts, e. g. Gene, Chromosome, Genotype, Phenotype, Population and fitness Function.
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OpenCE
Contrast Enhancement Techniques for low-light images
...OpenCE leverages a feature pyramid structure combined with a refinement stage to improve keypoint detection accuracy across multiple scales, particularly for challenging poses in crowded scenes. The repository includes training scripts, pretrained models, and testing code, allowing users to reproduce results reported in the paper. It supports standard human pose estimation benchmarks such as COCO, with configurations optimized for accuracy and efficiency. As an open resource, OpenCE offers researchers and practitioners a strong baseline for pose estimation and a foundation for extending CPN-based methods. -
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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. -
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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... -
Securing the Cloud Made EasyDesigned for organizations operating in the cloud who need complete, centralized visibility of their entire cloud estate and want more time and resources dedicated to remediating the actual risks that matter, Orca Security is an agentless cloud Security Platform that provides security teams with 100% coverage their entire cloud environment.
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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. -
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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. -
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...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/
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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... -
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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. -
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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. -
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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. -
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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). -
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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.
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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. -
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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. -
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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. ... -
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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. -
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PLaTHEA
People Localization and Tracking for HomE Automation
...The system acquires a stereo video stream from different kind of input devices included not-synchronized network cameras. An usage tutorial for an older is provided at http://www.dis.uniroma1.it/~leotta/demos/plathea/plathea.html. If you want to use this code please cite the research paper at https://onlinelibrary.wiley.com/doi/abs/10.1002/spe.2262. -
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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. -
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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
