Search Results for "algorithm" - Page 15
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Showing 1621 open source projects for "algorithm"
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xxhsum for Windows
xxhsum 0.8.0 - print or check xxHash non-cryptographic checksums
...Differences are: xxhsum doesn´t have text/binary mode switch (-b, -t); xxhsum always treats files as binary files; xxhsum has a hash bit width switch (-H); As xxHash is a fast non-cryptographic checksum algorithm, xxhsum should not be used for security related purposes. -
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DeepCluster
Deep Clustering for Unsupervised Learning of Visual Features
DeepCluster is a classic self-supervised clustering-based representation learning algorithm that iteratively groups image features and uses the cluster assignments as pseudo-labels to train the network. In each round, features produced by the network are clustered (e.g. k-means), and the cluster IDs become supervision targets in the next epoch, encouraging the model to refine its representation to better separate semantic groups. -
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ML.NET Samples
Samples for ML.NET, an open source and cross-platform machine learning
...The ML.NET CLI (command-line interface) is a tool you can run on any command prompt (Windows, Mac or Linux) for generating good quality ML.NET models based on training datasets you provide. In addition, it also generates sample C# code to run/score that model plus the C# code that was used to create/train it so you can research what algorithm and settings it is using. -
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TOTP Database
TOTP server side algorithm
calculate TOTP using database stored procedures allowing you to validate a user's entered TOTP with a stored secret. Cooperates with all authorization apps that calculate a TOTP using SHA1 encryption -
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CNN Explainer
Learning Convolutional Neural Networks with Interactive Visualization
...For example, an image classifier produces a class label (e.g, bird, plane) for what objects exist within an image. A convolutional neural network, or CNN for short, is a type of classifier, which excels at solving this problem! A CNN is a neural network: an algorithm used to recognize patterns in data. Neural Networks in general are composed of a collection of neurons that are organized in layers, each with their own learnable weights and biases. Let’s break down a CNN into its basic building blocks. A tensor can be thought of as an n-dimensional matrix. In the CNN above, tensors will be 3-dimensional with the exception of the output layer. ... -
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Computer Vision Pretrained Models
A collection of computer vision pre-trained models
...A pre-trained model may not be 100% accurate in your application. For example, if you want to build a self-learning car. You can spend years building a decent image recognition algorithm from scratch or you can take the inception model (a pre-trained model) from Google which was built on ImageNet data to identify images in those pictures. The model generates bounding boxes and segmentation masks for each instance of an object in the image. It's based on Feature Pyramid Network (FPN) and a ResNet101 backbone. TensorFlow implementation of 'YOLO: Real-Time Object Detection', with training and an actual support for real-time running on mobile devices. ... -
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Relative Overestimation VOP
VOP compression for MRI with overestimation control
...For better compression and speed use these: ***** https://sourceforge.net/projects/enhanced-sar-compression/ Virtual Observation Points SAR compression. Contains multiple Algorithms: Compression according to Eichfelder et al. and Lee et al. The Lee algorithm is enhanced by including overestimation control to reduce maximum relative overestimation. All algorithms are implemented in Matlab and were optimized for enhanced speed. Needs Matlab R2016b at least. Prefer R2018b or newer. ***** This work is outdated and is here for reference purpose, only. ***** If you are looking for improved SAR-compression algorithms, visit: https://sourceforge.net/projects/enhanced-sar-compression/ -
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SmillaEnlarger is a small graphical tool ( based on Qt ) to resize, especially magnify bitmaps in high quality. ( The used algorithm is an invention of my own )
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Seshat Naming and Balancing Service
Extended COS Naming and Balancing Service
...If you look up a balanced group you will transparently get a reference to an object in the group. The members of a group can be delivered either using a round robin or a random algorithm. The service uses Spring Security Framework for access control and can be configured to use any Authentication Authorization system supported by the Spring Security Framework. -
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COHCAP
City of Hope CpG Island Analysis Pipeline
COHCAP (City of Hope CpG Island Analysis Pipeline, pronounced "co-cap") is an algorithm to analyze single-nucleotide resolution methylation data (Illumina 450k methylation array, targeted BS-Seq, etc.). Please note: 1) The SourceForge version of COHCAP is no longer being updated. Please see the GitHub version: https://github.com/cwarden45/COHCAP This was the source repository for the Bioconductor version, with some changes after the decision to only provide the code through GitHub. 2) In addition to the original NAR paper, please see the following links: Benchmarks: http://www.nature.com/protocolexchange/protocols/2965#/introduction Protocol Exchange Files: http://sourceforge.net/projects/cohcap/files/Protocol_Exchange_Example.zip 3) Custom Annotation Files (including EPIC Array): https://sourceforge.net/projects/cohcap/files/additional_Bioconductor_annotations.zip/download -
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Jobber
An alternative to cron, with sophisticated status-reporting
...Sophisticated error handling: you can control whether and when a job is run again after it fails. For example, after an initial failure of a job, Jobber can schedule future runs using an exponential backoff algorithm. Sophisticated error reporting: you can control whether Jobber notifies you about each failed run, or only about jobs that have been disabled due to repeated failures. -
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Approximate Solution Finder
An open-source approximate logic design tool
We provide an open-source library of approximate multipliers described using Verilog HDL. The article related to the library is currently under review. -
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Rainflow
Fast rainflow counting written in C (C99)
Rainflow Counting Algorithm (4-point-method), C99 compliant. "Rainflow Counting" consists of four main steps: 1. Hysteresis Filtering 2. Peak-Valley Filtering 3. Discretization 4. Four Point Counting Method: These steps are fully documented in standards such as ASTM E1049 "Standard Practices for Cycle Counting in Fatigue Analysis" [1]. -
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A2RMS Algorithm
Implementation of the A2RMS Algorithm in Matlab
Implementation of the A2RMS Algorithm for univariate densities defined for real values. -
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java-string-similarity
Implementation of various string similarity and distance algorithms
...This was published by Masek in 1980 ("A Faster Algorithm Computing String Edit Distances"). -
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ngx_brotli
NGINX module for Brotli compression
ngx_brotli is a set of two Nginx modules developed by Google that enable Brotli compression for web content delivery. Brotli is a modern, general-purpose, lossless compression algorithm combining an optimized variant of LZ77, Huffman coding, and second-order context modeling. It provides compression ratios comparable to the best general-purpose compressors while maintaining speeds similar to Deflate (gzip). These modules help websites and APIs deliver smaller payloads, resulting in faster page loads, reduced bandwidth usage, and better Core Web Vitals. -
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SwiftOCR
Fast and simple OCR library written in Swift
SwiftOCR is a fast and simple OCR library written in Swift. It uses a neural network for image recognition. As of now, SwiftOCR is optimized for recognizing short, one-line long alphanumeric codes (e.g. DI4C9CM). We currently support iOS and OS X. If you want to recognize normal text like a poem or a news article, go with Tesseract, but if you want to recognize short, alphanumeric codes (e.g. gift cards), I would advise you to choose SwiftOCR because that's where it exceeds. Tesseract is... -
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Primitive Pictures
Reproducing images with geometric primitives
Primitive Pictures is an image processing command-line tool written in Go that reproduces images using geometric primitives (triangles, rectangles, ellipses, polygons, etc.). The core algorithm is iterative and “hill-climbing”: given a target image, it repeatedly finds the best single shape to add that will reduce the error between the current approximation and the target image, then draws that shape. Over time (e.g., adding 50-200 shapes) the output becomes an abstracted version of the input image—recognizable, artistic, and often visually striking. ... -
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Google2FA for Laravel
A One Time Password Authentication package
Google2FA is a PHP implementation of the Google Two-Factor Authentication Module, supporting the HMAC-Based One-time Password (HOTP) algorithm specified in RFC 4226 and the Time-based One-time Password (TOTP) algorithm specified in RFC 6238. -
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MADDPG
Code for the MADDPG algorithm from a paper
MADDPG (Multi-Agent Deep Deterministic Policy Gradient) is the official code release from OpenAI’s paper Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments. The repository implements a multi-agent reinforcement learning algorithm that extends DDPG to scenarios where multiple agents interact in shared environments. Each agent has its own policy, but training uses centralized critics conditioned on the observations and actions of all agents, enabling learning in cooperative, competitive, and mixed settings. The code is built on top of TensorFlow and integrates with the Multiagent Particle Environments (MPE) for benchmarking. ... -
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Cubature.jl
One- and multi-dimensional adaptive integration routines for Julia
This module provides one- and multi-dimensional adaptive integration routines for the Julia language, including support for vector-valued integrands and facilitation of parallel evaluation of integrands, based on the Cubature Package by Steven G. Johnson. Adaptive integration works by evaluating the integrand at more and more points until the integrand converges to a specified tolerance (with the error estimated by comparing integral estimates with different numbers of points). The Cubature... -
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AUDACITY
AUtozygosity iDentification And ClassIfication Tool
AUDACITY is novel computational approach for the identification of Runs of Homozygosity by using VCF files from whole-exome and whole-genome sequencing data generated by second generation sequencing technologies. AUDACITY is a tool integrating novel RoH detection algorithm and autozygosity prediction score for prioritization of mutation-surrounding regions. ###################################################################### The AUDACITY tool has been published on Computational and Structural Biotechnology Journal (CSBJ). . You can find it at https://www.sciencedirect.com/science/article/pii/S2001037020303354 ###################################################################### -
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Flip card learning program for iPhone with a spaced learning algorithm. Create your own databases and edit the cards directly on the iPhone. Import Palm databases or csv-formatted files and backup your data with our Java application.
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DarkF
DarkF is an FFT optical simulation code for GW inteferometers
DarkF is an optical simulation code in FORTRAN 90 able to represent with a high accuracy any kind of stable cavity, even when many static or dynamical defects are present, like misalignments, curvature errors, surface irregularities, substrate inhomogeneities. It uses a plane wave decomposition to propagate the wavefronts. Beams and mirrors are sampled on a grid of coordinates (x; y) and the DarkF resolution is depending on the grid size and on the sampling rate (typically a size of 0.6m... -
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KCP
A fast and reliable ARQ protocol
KCP is a fast and reliable protocol that can achieve the transmission effect of a reduction of the average latency by 30% to 40% and reduction of the maximum delay by a factor of three, at the cost of 10% to 20% more bandwidth wasted than TCP. It is implemented by using the pure algorithm, and is not responsible for the sending and receiving of the underlying protocol (such as UDP), requiring the users to define their own transmission mode for the underlying data packet, and provide it to KCP in the way of callback. Even the clock needs to be passed in from the outside, without any internal system calls. The entire protocol has only two source files of ikcp.h, ikcp.c, which can be easily integrated into the user's own protocol stack. ...
