Search Results for "multi-system" - Page 71
Sort By:
Showing 2682 open source projects for "multi-system"
View related business solutions-
Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
-
99.99% Uptime for MySQL and PostgreSQL DatabasesCloud SQL Enterprise Plus delivers near-zero downtime with 35 days of point-in-time recovery. Supports MySQL, PostgreSQL, and SQL Server.
-
1
vid2vid
Pytorch implementation of our method for high-resolution
...Built on top of image-to-image translation techniques like pix2pixHD, it extends these ideas into the temporal domain by ensuring consistency across video frames. The system can synthesize complex outputs such as realistic talking faces, human motion animations, or dynamic street scenes by learning temporal relationships between frames. It uses generative adversarial networks combined with temporal modeling strategies to maintain coherence and reduce flickering artifacts. The framework is capable of producing high-resolution outputs and is widely used in research related to video synthesis, animation, and simulation. ... -
2
Facets
Visualizations for machine learning datasets
The power of machine learning comes from its ability to learn patterns from large amounts of data. Understanding your data is critical to building a powerful machine learning system. Facets contains two robust visualizations to aid in understanding and analyzing machine learning datasets. Get a sense of the shape of each feature of your dataset using Facets Overview, or explore individual observations using Facets Dive. Explore Facets Overview and Facets Dive on the UCI Census Income dataset, used for predicting whether an individual’s income exceeds $50K/yr based on their census data. ... -
3
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. -
4
TIES
A smart search engine for medical documents
TIES (Text Information Extraction System) is a clinical text search engine that uses Natural Language Processing techniques to extract medical concepts from free text clinical reports. It provides secure de-identified access to this information and has in built collaboration tools and honest broker functionality. It is licensed for academic use under the BSD license. For commercial use please contact Nexi at http://nexihub.com *** NOTICE: this software and forum are no longer maintained, as of 8/15/2019. ... -
Cut Data Warehouse Costs by 54%BigQuery delivers 54% lower TCO with exabyte scale and flexible pricing. Free migration tools handle the SQL translation automatically.
-
5
CakeChat
CakeChat: Emotional Generative Dialog System
CakeChat is a backend for chatbots that are able to express emotions via conversations. The code is flexible and allows to condition model's responses by an arbitrary categorical variable. For example, you can train your own persona-based neural conversational model or create an emotional chatting machine. Hierarchical Recurrent Encoder-Decoder (HRED) architecture for handling deep dialog context. Multilayer RNN with GRU cells. The first layer of the utterance-level encoder is always... -
6
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. -
7
TGAN
Generative adversarial training for generating synthetic tabular data
...TGAN has been developed and runs on Python 3.5, 3.6 and 3.7. Also, although it is not strictly required, the usage of a virtualenv is highly recommended in order to avoid interfering with other software installed in the system where TGAN is run. For development, you can use make install-develop instead in order to install all the required dependencies for testing and code listing. In order to be able to sample new synthetic data, TGAN first needs to be fitted to existing data. -
8
MultiPathNet
A Torch implementation of the object detection network
...It extends the Fast R-CNN framework by introducing multiple network “paths” to enhance feature extraction and object recognition robustness. The MultiPath architecture incorporates skip connections and multi-scale processing to capture both fine-grained details and high-level context within a single detection pipeline. This results in improved detection accuracy across various object sizes and categories compared to standard single-path architectures. The repository supports training, evaluation, and visualization for object detection tasks on popular datasets such as PASCAL VOC and MS COCO. ... -
9
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.
-
AI-powered service management for IT and enterprise teamsGive your IT, operations, and business teams the ability to deliver exceptional services—without the complexity. Maximize operational efficiency with refreshingly simple, AI-powered Freshservice.
-
10
spark-ml-source-analysis
Spark ml algorithm principle analysis and specific source code
...The project aims to help developers and data scientists understand how distributed machine learning algorithms are implemented and optimized inside the Spark ecosystem. Instead of providing a runnable software system, the repository focuses on explaining algorithm principles and examining the underlying source code used in Spark’s machine learning package. The repository contains detailed analyses of various algorithms including classification, regression, clustering, dimensionality reduction, and recommendation systems. Each section discusses both the mathematical principles behind the algorithms and how Spark implements them in a distributed computing environment. ... -
11
newLISP for BSDs, LINUX, MacOS X, SunOS and Win32: small, fast 350+ functions, a -C-, MySQL, PostgreSQL, SQLite, ODBC, TCP/IP, UDP, XML, Java interface, string processing, regular expressions , math, financial, statistical functions, Win32 DLL
-
12
Multidimensional Neural Network
Multidimensional Neural Network
...Solution to lower its magnitude is to use Not Fully Connected Neural Network, when that is the case than with which neurons from previous layer neuron is connected has to be considered. The simplest solution would be to use Cartesian Coordinate System, and treat layers as one dimensional lines or two dimensional rectangles or three, four, five ... dimensional cuboids. In that model each neuron in layer is connected to neurons in its surrounding in previous layer. -
13
Scalable Distributed Deep-RL
A TensorFlow implementation of Scalable Distributed Deep-RL
...The learner uses importance weighting to correct for policy lag between actors and the learner, enabling stable off-policy training at scale. This design allows the system to scale efficiently to hundreds of environments and billions of frames while maintaining sample efficiency and stability. The implementation supports training in DeepMind Lab (DMLab) and has also been adapted for other environments like Atari and Street View. -
14
DetectAndTrack
The implementation of an algorithm presented in the CVPR18 paper
DetectAndTrack is the reference implementation for the CVPR 2018 paper “Detect-and-Track: Efficient Pose Estimation in Videos,” focusing on human keypoint detection and tracking across video frames. The system combines per-frame pose detection with a tracking mechanism to maintain identities over time, enabling efficient multi-person pose estimation in video. Code and instructions are organized to replicate paper results and to serve as a starting point for researchers working on pose in video. Although the repo has been archived and is now read-only, its issue tracker and artifacts remain useful for understanding implementation details and experimental settings. ... -
15
Delphi Face Recognition March_01_2019
Delphi Face Recognition
...Donate and message or mail at dbinxecod@gmail.com RTSP url link updated BUG FIXED! MEMORY LEAK! ADDED 64BIT + TBB HARD BOILED FACE RECOGNITION: https://sourceforge.net/projects/delphi-face-recognizer/ Gate ID Multi Face Recognition: $384 https://sourceforge.net/projects/opencv-multi-face-detect/ Delphi Face Detection: FREE Source code! https://sourceforge.net/projects/delphi-opencv-face-detection/ Works on IP Camera using RTSP. Runs on Windows XP to Windows 10 using SQLite Dataface! You can reprogram / setup / configure / scale the Face Recognition accuracy! ... -
16
TextRank
TextRank implementation for Python 3
TextRank is an implementation of the TextRank algorithm for extractive text summarization and keyword extraction, inspired by Google’s PageRank. -
17
DeepTraffic
DeepTraffic is a deep reinforcement learning competition
DeepTraffic is a deep reinforcement learning simulation designed to teach and evaluate autonomous driving algorithms in a dense highway environment. The system presents a simulated multi-lane highway where an AI-controlled vehicle must navigate traffic while maximizing speed and avoiding collisions. Participants design neural network policies that determine the vehicle’s actions, such as accelerating, decelerating, changing lanes, or maintaining speed. The project was created as part of an educational competition associated with MIT’s deep learning courses, encouraging students and researchers to experiment with reinforcement learning techniques. ... -
18
howmanypeoplearearound
Count the number of people around you by monitoring wifi signals
howmanypeoplearearound calculates the number of people in the vicinity using the approximate number of smartphones as a proxy (since ~70% of people have smartphones nowadays). A cellphone is determined to be in proximity to the computer based on sniffing WiFi probe requests. Possible uses of howmanypeoplearearound include, monitoring foot traffic in your house with Raspberry Pis, seeing if your roommates are home, etc. There are a number of possible USB WiFi adapters that support monitor... -
19
DeepMask
Torch implementation of DeepMask and SharpMask
DeepMask is an early, influential approach to class-agnostic object segmentation that learns to propose pixel-accurate masks directly from images. Instead of first generating boxes and then refining them, the network predicts a foreground mask and an “objectness” score for a given image patch, yielding high-quality segment proposals suitable for downstream detection or instance segmentation. The model is trained end-to-end to align mask shape with object extent, which markedly improves... -
20
Tensorpack
A Neural Net Training Interface on TensorFlow, with focus on speed
...On common CNNs, it runs training 1.2~5x faster than the equivalent Keras code. Your training can probably gets faster if written with Tensorpack. Scalable data-parallel multi-GPU / distributed training strategy is off-the-shelf to use. Squeeze the best data loading performance of Python with tensorpack.dataflow. Symbolic programming (e.g. tf.data) does not offer the data processing flexibility needed in research. Tensorpack squeezes the most performance out of pure Python with various auto parallelization strategies. ... -
21
NASH OS
Nash Operating System for Modern Ecommerce
The all-built-in-one, automatic, ready-to-go out-of-box, easy-to-use state-of-the-art, and really awesome NASH OS! Over 25,000+ flexible features and controls and all scalable!! The most powerful solution ever built to instantly deliver new heights of online ecommerce enterprise to you. -
22
C++Builder Face Recognition March01_2019
C++Builder Face Recognition
...https://sourceforge.net/projects/delphi-face-recognizer/ C++Builder Face Detection: FREE Source code! https://sourceforge.net/p/cbuilder-opencv-face-detection/ For Live: Face Attendance System, Facial Emotion, Gender Recognition Works on IP Camera using RTSP. ---> After you Donate, message or mail at dbinXecod@gmail.com ---> Runs on Windows XP to Windows 10 using SQLite Dataface! You can reprogram / setup / configure / scale the Face Recognition accuracy! Delphi Face Detection: FREE Source code! ... -
23
Virtual Laboratory Environment
A multi-modeling and simulation environment to study complex systems
VLE is a multi-modeling and simulation environment to study complex dynamic systems. VLE is based on the discrete event specification DEVS. and it implements the DSDE formalism (A merge of Dynamic Structure DEVS, DSDEVS, with Parallel DEVS, PDEVS). VLE provides a complete set of C++ libraries, called VFL (VLE Foundation Libraries), to develop DEVS models, to gets results of simulations, to launch simulation on cluster. -
24
qqbot
A conversation robot base on Tencent's SmartQQ
...When the next startup, you can enter: qqbot -q qq number , first try to restore the login information from the local file (no need to scan the code manually), only if the recovery fails Only when the login information is successful or the login information has expired will you need to scan the QR code to log in manually. Generally, saved login information will expire after 2 days. Under Linux, the gvfs-open or shotwell command is required in the system to automatically pop up the QR code image (generally, the system with the GNOME virtual file system gvfs installed will contain one of these two commands). -
25
EECluster
Tool for energy-efficient resource management in HPC clusters
EECluster is software tool for managing the energy-efficient allocation of the cluster resources. EECluster uses a Hybrid Genetic Fuzzy System as the decision-making mechanism that elicits part of its rule base dependent on the cluster workload scenario, delivering good compliance with the administrator preferences. In the latest version, we leverage a more sophisticated and exhaustive model that covers a wider range of environmental aspects and balances service quality and power consumption with all indirect costs, including hardware failures and subsequent replacements, measured in both monetary units and carbon emissions. ...
