Search Results for "bns-tools" - Page 50
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Showing 2182 open source projects for "bns-tools"
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MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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Enterprise-grade ITSM, for every businessFreshservice is an intuitive, AI-powered platform that helps IT, operations, and business teams deliver exceptional service without the usual complexity. Automate repetitive tasks, resolve issues faster, and provide seamless support across the organization. From managing incidents and assets to driving smarter decisions, Freshservice makes it easy to stay efficient and scale with confidence.
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Decentralized-Internet
A SDK/library for decentralized web and distributing computing project
The Decentralized-Internet project by Lonero Team is a software development kit (SDK) and library aimed at facilitating the creation of decentralized web and distributed computing applications. It provides developers with tools to build applications that operate independently of centralized servers, promoting a more open and resilient internet infrastructure. -
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VGGFace2
VGGFace2 Dataset for Face Recognition
...These models achieve strong verification performance on benchmarks such as IJB-B and include variants with lower-dimensional embeddings for compact feature representation. The project also includes preprocessing tools, face detection scripts, and etc. -
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QtiPlot is a user-friendly, platform independent data analysis and visualization application similar to the non-free Windows program Origin.
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VoteNet
Deep Hough Voting for 3D Object Detection in Point Clouds
VoteNet is a 3D object detection framework for point clouds that combines deep point set networks with a Hough voting mechanism to localize and classify objects in 3D space. It tackles the challenge that object centroids in 3D scenes often don’t lie on any input surface point by having each point “vote” for potential object centers; these votes are then clustered to propose object hypotheses. Once cluster centers are formed, the network regresses bounding boxes around them and classifies... -
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ChainerRL
ChainerRL is a deep reinforcement learning library
ChainerRL (this repository) is a deep reinforcement learning library that implements various state-of-the-art deep reinforcement algorithms in Python using Chainer, a flexible deep learning framework. PFRL is the PyTorch analog of ChainerRL. ChainerRL has a set of accompanying visualization tools in order to aid developers' ability to understand and debug their RL agents. With this visualization tool, the behavior of ChainerRL agents can be easily inspected from a browser UI. Environments that support the subset of OpenAI Gym's interface (reset and step methods) can be used. -
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Top deep learning Github repositories
Top 200 deep learning Github repositories sorted by stars
...The repository categorizes projects related to neural networks, computer vision, natural language processing, reinforcement learning, and other areas of artificial intelligence. By collecting popular open-source implementations in one place, the project simplifies the process of exploring cutting-edge tools and research implementations for deep learning practitioners. The curated lists are particularly helpful for developers who want to quickly identify well-maintained projects with strong community support. -
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HDL Checker
Repurposing existing HDL tools to help writing better code
HDL Checker is a language server that wraps VHDL/Verilg/SystemVerilog tools that aims to reduce the boilerplate code needed to set things up. It supports Language Server Protocol or a custom HTTP interface; can infer the library VHDL files likely to belong to, besides working out mixed language dependencies, compilation order, interpreting some compiler messages and providing some (limited) static checks. -
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CTOSC
Tools for processing solar cell characterization data (Rsh,ECV,QSSPC)
CTOSC stands for 'Characterization Toolbox for Solar Cells' and contains a few functionalities to process solar cell data: sheet resistance mapping, making ECV data graphs, QSSPC lifetime data graphs and showing/averaging PL/EL images. For ECV/Rsh/QSSPC data the program currently supports output files from the Sunlab Sherescan four-point probe (.txt), the WEP Wafer Profiler CVP21 (.csv) and Sinton WCT-120 (.txt). -
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PBTK Optimizer
Application for optimization of parameters in PBTK models
Physiologically based toxicokinetic (PBTK) modeling offers great promise in environmental risk assessment, potentially speeding up dose-response studies while minimizing animal testing. Some limitations exist in the PBTK field, such as difficulty of model development and a lack of application specific software tools to help modelers. Some parameters used in PBTK models, such as tissue weights, are easily measure. Other parameters can be determined through in-vitro experiments or through extrapolation using published equations. When it is impractical to use these methods to estimate a parameter, techniques can be used to optimize parameters so that model results best fit validation data. ... -
Fully Managed MySQL, PostgreSQL, and SQL ServerCloud SQL handles your database ops end to end, so you can focus on your app.
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Graph Nets library
Build Graph Nets in Tensorflow
...A graph network takes graphs as inputs, consisting of edges, nodes, and global attributes, and produces updated graphs with modified feature representations at each level. This library implements the foundational ideas from DeepMind’s paper “Relational Inductive Biases, Deep Learning, and Graph Networks”, offering tools to explore relational reasoning and message-passing neural networks. Graph Nets supports both TensorFlow 1 and TensorFlow 2, working with CPU and GPU environments, and includes educational Jupyter demos for shortest path finding, sorting, and physical prediction tasks. The codebase emphasizes modularity, allowing users to easily define their own edge, node, and global update functions. -
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Web Security Dojo
Virtual training environment to learn web app ethical hacking.
Web Security Dojo is a virtual machine that provides the tools, targets, and documentation to learn and practice web application security testing. A preconfigured, stand-alone training environment ideal for classroom and conferences. No Internet required to use. Ideal for those interested in getting hands-on practice for ethical hacking, penetration testing, bug bounties, and capture the flag (CTF). -
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C++QED
A framework for simulating open quantum dynamics
...The basic idea is to allow users to build arbitrarily complex interacting quantum systems out of free subsystems and interactions (elements), and simulate their time evolution with a number of available time-evolution drivers. C++QEDv2 specifies a small grammar to describe composite quantum systems. Apart from providing a number of elements out of the box, there are tools which facilitate the implementation of new elements. These are being added continuously, as the need arises. The principal concept of the design of C++QEDv2 is that all information available at compile time should be processed as such, with the help of TMP. The framework is very sensitive to performance both in computer resources and coding/design. -
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v2rayL
v2ray linux GUI
V2Ray is a tool under Project V. Project V includes a series of tools to help you create your own customized network system. And V2Ray belongs to the core one. Simply put, V2Ray is a proxy software similar to Shadowsocks, but has more advantages than Shadowsocks.v2ray linux client, using pyqt5 to write GUI interface, the core is based on v2ray-core (v2ray-linux-64) vmess supports websocket, mKcp, and tcp. -
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SMAC
SMAC: The StarCraft Multi-Agent Challenge
SMAC (StarCraft II Multi-Agent Challenge) is a benchmark environment for cooperative multi-agent reinforcement learning (MARL), based on real-time strategy (RTS) game scenarios in StarCraft II. It allows researchers to test algorithms where multiple units (agents) must collaborate to win battles against built-in game AI opponents. SMAC provides a controlled testbed for studying decentralized execution and centralized training paradigms in MARL. -
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DisplayCAL
Display Calibration and Characterization powered by Argyll CMS
DisplayCAL (formerly known as dispcalGUI) is a graphical user interface for the display calibration and profiling tools of Argyll CMS, an open source color management system. Calibrate and characterize your display devices using one of the many supported measurement instruments, with support for multi-display setups and a variety of available settings like customizable whitepoint, luminance, tone response curve as well as the option to create accurate look-up-table ICC profiles as well as some proprietary 3D LUT formats. ... -
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VulnX
Intelligent Bot, Shell can achieve automatic injection
...Vulnx is An Intelligent Bot Auto Shell Injector that detects vulnerabilities in multiple types of Cms, fast cms detection, information gathering, and vulnerability scanning of the target like subdomains, IP addresses, country, org, timezone, region, and more. Instead of injecting each and every shell manually as all the other tools do, VulnX analyses the target website checking the presence of a vulnerability if so the shell will be Injected by searching URLs with the dorks Tool. Detects CMS (wordpress, joomla, prestashop, drupal, opencart, magento, lokomedia). -
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QMForge reads output from various quantum mechanical calculations and provides tools for analyzing these results. Specifically, population (Mulliken and C-squared), fragment, and charge decomposition analyses are available. See https://qmforge.net for more info.
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YouTube-8M
Starter code for working with the YouTube-8M dataset
youtube-8m is Google’s open source starter code and reference implementation for training and evaluating machine learning models on the YouTube-8M dataset, one of the largest video understanding datasets publicly released. The repository provides a complete pipeline for video-level and frame-level modeling using TensorFlow, including data reading, model training, evaluation, and inference. It was developed to support the YouTube-8M Video Understanding Challenge (hosted on Kaggle and featured... -
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PyTorch-BigGraph
Generate embeddings from large-scale graph-structured data
...Its training loop is built for throughput: asynchronous I/O, memory-mapped tensors, and lock-free updates keep GPUs and CPUs fed even at extreme scale. The toolkit includes evaluation metrics and export tools so learned embeddings can be used in downstream nearest-neighbor search, recommendation, or analytics. In practice, PBG’s design lets practitioners train high-quality graph embeddings. -
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yz-next-apyref
Arno-Can's Python based API Reference Generator.
Multi-Syntax-Version and Multi-Implementation API reference documentation generator. Supports local and remote sources. -
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NiftyNet
An open-source convolutional neural networks platform for research
...NiftyNet’s modular structure is designed for sharing networks and pre-trained models. Using this modular structure you can get started with established pre-trained networks using built-in tools. Adapt existing networks to your imaging data. Quickly build new solutions to your own image analysis problems. NiftyNet currently supports medical image segmentation and generative adversarial networks. NiftyNet is not intended for clinical use. -
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yapydata
Lower-Layer unified data - JSON, XML, YAML + INI, CFG, properties
...Therefore it encapsulates the libraries by offering a common API with the canonical internal data as JSON compatible Python in-memory structure. The application is foreseen in particular for the lower layer of the software stack including setup-tools. Thus it uses standard libraries only whenever possible. The initial supported DDLs are: * JSON, XML, YAML and the formats * INI, CFG, .properties The yapydata in particular supports the advanced access to data entries by mapping the dotted-OID notation onto mixed in-memory data types, optional including non-conformant tyeps such as tuple and set. -
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ELI5
A library for debugging/inspecting machine learning classifiers
ELI5 is a Python library designed to help developers interpret, debug, and explain the predictions of machine learning models. The project focuses on improving model transparency by providing tools that visualize feature importance and prediction reasoning. It supports several popular machine learning frameworks including scikit-learn, XGBoost, LightGBM, CatBoost, and Keras. The library allows users to inspect model weights, analyze decision trees, and compute permutation feature importance for black-box models. It also provides specialized tools such as TextExplainer, which can highlight important words in text classification tasks to explain why a model produced a particular prediction. ... -
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Neural MMO
Code for the paper "Neural MMO: A Massively Multiagent Game..."
Neural MMO is a massively multi-agent simulation environment developed by OpenAI for reinforcement learning research. It provides a persistent, procedurally generated world where thousands of agents can interact, compete, and cooperate in real time. The environment is inspired by Massively Multiplayer Online Role-Playing Games (MMORPGs), featuring resource gathering, combat mechanics, exploration, and survival challenges. Agents learn behaviors in a shared ecosystem that supports long-term... -
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An open source framework for LC-MS based proteomics and metabolomics. OpenMS offers data structures and algorithms for the processing of mass spectrometry data. The library is written in C++. Our source code and wiki lives on GitHub (https://github.com/OpenMS/OpenMS).
