Search Results for "network"
Sort By:
Showing 67 open source projects for "network"
View related business solutions-
Gemini 3 and 200+ AI Models on One PlatformBuild, govern, and optimize agents and models with Gemini Enterprise Agent Platform.
-
Forever Free Full-Stack Observability | Grafana CloudBuilt on open standards like Prometheus and OpenTelemetry, Grafana Cloud includes Kubernetes Monitoring, Application Observability, Incident Response, plus the AI-powered Grafana Assistant. Get started with our generous free tier today.
-
1
NeuroJSON
Scalable, searchable and verifiable neuroimaging data exchange platfor
-
2
Algorithms Math Models
MATLAB implementations of algorithms
Algorithms_MathModels is a large MATLAB collection of algorithms and solved examples targeted at students and teams preparing for mathematical modeling competitions (national and international contests like MCM/ICM). The repository gathers implementations and case studies across many topics commonly used in contest solutions: optimization (linear, integer, goal and nonlinear programming), heuristic and metaheuristic methods (simulated annealing, genetic algorithms, immune algorithms), neural... -
3
MTCNN Face Detection Alignment
Joint Face Detection and Alignment
MTCNN_face_detection_alignment is an implementation of the “Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Networks” algorithm. The algorithm uses a cascade of three convolutional networks (P-Net, R-Net, O-Net) to jointly detect faces (bounding boxes) and align facial landmarks in a coarse-to-fine manner, leveraging multi-task learning. Non-maximum suppression and bounding box regression at each stage. The repository includes Caffe / MATLAB code, support scripts,... -
4
DnCNN
Beyond a Gaussian Denoiser: Residual Learning of Deep CNN
This repository implements DnCNN (“Deep CNN Denoiser”) from the paper “Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising”. DnCNN is a feedforward convolutional neural network that learns to predict the residual noise (i.e. noise map) from a noisy input image, which is then subtracted to yield a clean image. This formulation allows efficient denoising, supports blind Gaussian noise (i.e. unknown noise levels), and can be extended to related tasks like image super-resolution or JPEG deblocking in some variants. ... -
Compliant and Reliable File Transfers Backed by Top Security CertificationsStop relying on non-certified, legacy file transfer tools that creak under the weight of modern security demands. Get full audit trails, advanced access controls and more supported by an award-winning team of experts. Start your free 25-day trial today.
-
5
VRN
Code for "Large Pose 3D Face Reconstruction
The network is unguided (no 2D landmarks as intermediate). The mesh surfaces can be textured (in MATLAB branch) and colored. Docker container provided for easy CPU deployment. -
6
Cantera is a suite of object-oriented software tools for problems involving chemical kinetics, thermodynamics, and/or transport processes. It can be used from MATLAB, Python, C++, or Fortran.
-
7
cnn-for-image-retrieval is a research-oriented project that demonstrates the use of convolutional neural networks (CNNs) for image retrieval tasks. The repository provides implementations of CNN-based methods to extract feature representations from images and use them for similarity-based retrieval. It focuses on applying deep learning techniques to improve upon traditional handcrafted descriptors by learning features directly from data. The code includes training and evaluation scripts that...
-
8
ConvNet Burden
Memory consumption and FLOP count estimates for convnets
...Support for multiple network definitions/architectures. Estimation of memory consumption (e.g. feature map sizes, parameter storage). Estimation of FLOPs (floating point operations) for CNN architectures. -
9
SFD
S³FD: Single Shot Scale-invariant Face Detector, ICCV, 2017
S³FD (Single Shot Scale-invariant Face Detector) is a real-time face detection framework designed to handle faces of various sizes with high accuracy using a single deep neural network. Developed by Shifeng Zhang, S³FD introduces a scale-compensation anchor matching strategy and enhanced detection architecture that makes it especially effective for detecting small faces—a long-standing challenge in face detection research. The project builds upon the SSD framework in Caffe, with modifications tailored for face detection tasks. ... -
Try Google Cloud Risk-Free With $300 in CreditUse your credit across every product. Compute, storage, AI, analytics. When it runs out, 20+ products stay free. You only pay when you choose to.
-
10
Faster R-CNN
Object detection framework based on deep convolutional networks
This repository provides a MATLAB / Caffe re-implementation of the Faster R-CNN object detection framework (originally from Ren et al. 2015). The Faster R-CNN architecture combines a Region Proposal Network (RPN) with a Fast R-CNN style detection network to share convolutional feature maps and thus speed up detection. The repo includes code to train, test, and deploy Faster R-CNN models under the MATLAB / Caffe environment, example configuration files, and model checkpoints. Multiple configuration files for different datasets and architectures. ... -
11
OpenCE
Contrast Enhancement Techniques for low-light images
OpenCE is an open source implementation of the paper Cascaded Pyramid Network for Multi-Person Pose Estimation (CVPR 2018) by Yilun Chen, Zhicheng Wang, Yuxiang Peng, Zhiqiang Zhang, Gang Yu, and Jian Sun. The framework provides a complete training and evaluation pipeline for human pose estimation using a cascaded pyramid network (CPN). 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. ... -
12
The purpose of the Freely Moving Animal (FMA) Toolbox is to help analyze electrophysiological and behavioral data recorded from freely moving animals.
-
13
GTK+ IOStream
GTK+iostream, Data plots, ORB, Neural Networks, WSOLA
Create GTK+ interfaces using IOStream style code. Its simple and quick! Also providing simple data plotting (similar to Matlab/Octave), ORB (Object Request Broker), and Neural Network computations. You can create GTK+ GUIs in a few lines of code. Labels<<"Thanks for reading"; (HBox<<Labels).show(); or even one line : (HBox() << (Labels()<<"Thanks for reading")).show(); Inline code destructs the classes, but leaves the widgets/callbacks operating. This is great for embedded memory saving code. ... -
14
Face Verification Experiment
Original Caffe Version for LightCNN-9. Highly recommend to use PyTorch
face_verification_experiment is a research repository focused on experiments in face verification using deep learning. It provides implementations and scripts for testing different neural network architectures and training strategies on face recognition and verification tasks. The project is designed to help researchers and practitioners evaluate the performance of models on standard datasets and explore techniques for improving accuracy. By offering experimental setups, it enables reproducibility and comparative study of face verification approaches. ... -
15
MetaMIS
Metagenomic Microbial Interaction Simulator
MetaMIS is the first tool to automatically infer the microbial interactions of microbial community profile in the field of metagenomics. The most distinguished feature of MetaMIS is its ability to retain maximum population of rare species in an ecological interactive network. MetaMIS provides a user-friendly interactive stand-alone graphical interface for scientists without programming skills to investigate the interactions among microorganisms. 2017.03.09 MetaMIS_v1.02: - Create an option to export consensus table. - Decimal time is allowed. 2016.12.16 MetaMIS_v1.01: - fix the memory-out problem for larger abundance table (>500 OTUs)... -
16
CRFasRNN
Semantic image segmentation method described in the ICCV 2015 paper
CRF-RNN is a deep neural architecture that integrates fully connected Conditional Random Fields (CRFs) with Convolutional Neural Networks (CNNs) by reformulating mean-field CRF inference as a Recurrent Neural Network. This fusion enables end-to-end training via backpropagation for semantic image segmentation tasks, eliminating the need for separate, offline post-processing steps. Our work allows computers to recognize objects in images, what is distinctive about our work is that we also recover the 2D outline of objects. Currently we have trained this model to recognize 20 classes. ... -
17
SILA
Automated bacterial and archaeal genome annotation system
SILA is a system for automated annotation of bacterial and archaeal genomes. It provides accurate gene prediction using a combination of tools (Prodigal and HGF) and a web site for task management and visualization of annotation. This project is in alpha stage. Please use the online service available at: http://www.bioinfo.ufpr.br/SILA/login.jsp Documentation (portuguese only): http://hdl.handle.net/1884/34801 -
18
BiRW
Bi-random Walks for Phenome-Genome Association Prediction
...The processed OMIM human disease phenotype-gene association network and MGI mouse phentoype-gene association network are also released together with the source code. -
19
K-Level 2.0 [revised]
An application of leveling network adjustment using Matlab
This is an application of leveling network adjustment based on Matlab. The method used in this application is least square adjustment. User can enter the leveling data directly or by reading a text file. -
20
-
21
igafem
Open source 3D Matlab Isogeometric Analysis Code
...The tight coupling of CAD and analysis within IGA requires knowledge from both fields and it is one of the goals of the MIGFEM is to provide a simple-to-understand IGA FEM code. The work is funded under the FP7 Initial Training Network Funding under grant number 289361 'Integrating Numerical Simulation and Geometric Design Technology.' If you use this code or inspired by it please cite the following reference in your work: VP Nguyen, C Anitescu, S Bordas, T Rabczuk. "Isogeometric analysis: an overview and computer implementation aspects". Mathematics and Computers in Simulation, (2015), pp. 89-116, Vol 117. -
22
Locaviewer
Sistema de vídeo distribuido para Centros Infatiles
Proyecto para la IV Edición del Desafío Tecnológico planteado en la ETSIIT de la Universidad de Granada. Nuestro grupo propone una solución para que padres puedan ver en tiempo real a sus hijos mientras se encuentran Centros Infantiles. Nuestro producto se diferencia de otros en el que el cambio de cámara es automático, realizando para ello una triangulación de los niños. -
23
nail_systems_biology
NAIL is a toolset for network analysis in the life sciences
The NAIL (Network Analysis and Inference Library) project is a set of tools for solving problems in the life sciences using network (graph) approaches. NAIL includes methods for creating networks, analysing and comparing networks, and for visualising or presenting the results. These methods are designed as self-contained platform-independent components which can be called either from another program, or from a command line. -
24
Rcnn
R-CNN: Regions with Convolutional Neural Network Features
This repository contains the original MATLAB implementation of R-CNN (Regions with Convolutional Neural Networks), a pioneering deep learning-based object detection framework. Developed by Ross Girshick, R-CNN combines region proposals with convolutional neural networks to detect objects in images. It was one of the first approaches to significantly improve performance on object detection benchmarks like PASCAL VOC. -
25
METAlab GTG
Matlab toolbox to run a GLM on graph theoretic properties in MRI data
This Matlab toolbox runs a GLM on graph theoretic network properties in brain networks. The GLM accepts continuous & categorical between-participant predictors and categorical within-participant predictors. Significance is determined via non-parametric permutation tests. The toolbox allows testing of both fully connected and thresholded networks (based on a range of thresholds). The toolbox also provides a data processing path for resting state fMRI data.
