Search Results for "segmentation" - Page 8
Sort By:
Showing 329 open source projects for "segmentation"
View related business solutions-
$300 Free Credits for Your Google Cloud ProjectsLaunch your next project with $300 in free Google Cloud credits—no strings attached. Test, build, and deploy without risk. Use your credits across the entire Google Cloud platform to find what works best for your needs. After your credits are used, continue with always-free tier services. Only pay when you're ready to scale. Sign up in minutes and start exploring.
-
Stop Cyber Threats with VM-Series Next-Gen Firewall on AzureGain integrated visibility across all traffic in a single pass. Deploy Palo Alto Networks VM-Series to determine application identity and content while automating security policy updates via rich APIs.
-
1
Batch PIE
A batch pipelined image editor
Current filter functionality: - Simple editing options: Image cropping, resizing, rotation, Color brightness curve alignment - Histobram processing: Convolution, statistics (e. g. f_max or median analysis) - Image segmentation: The actual segmentation process as well as group weight calculation for further filtering (both functions rely on self defined custom dynamic mathematical functions) - Dynamic mathematical functions for custom and automated image filtering: General mathematical operations, using image or matrix as f(x, y), export f(x, y) as image or matrix, mapping variables on other ones and of course boolean operation for case sensitivity - A flexible variables model of dynamic mathematical function that sets no restriction on particular variables count - Sub project support for an organized total process targeting to save time using previously created editing routines instead of redoing steps each time -
2
Deep Learning for Medical Applications
Deep Learning Papers on Medical Image Analysis
...The repository may also contain domain-specific modules: loss functions like Dice, focal loss, metrics such as sensitivity/recall/IoU, and visualization utilities for overlaying segmentation masks. -
3
CodelPlant
Codelplant stat. multi-regression M-learning for leaves segmentation
CodelPlant is based on the creation of a statistical multi-regression decision tree from data obtained by pixel RGB-HSB machine learning analysis. The model is training with human observation, so the human factor is being entered the process. -
4
bwfinder
Exogenous feature extractor from brainwaves
This program for Scilab searches for primary peaks in the segments of brainwave signal spectrum which are much above the signal spectrum average. Brainwave segments of 1 s are Fourier transformed, thresholded and merged if contiguous. Selected segments are drawn in time domain, frequency domain and a narrow-band analysis at 75 Hz is attempted. This program should detect strong external signals in brainwave recordings. Weak signals are not detected. This program requires the "edf2ascii"... -
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.
-
5
CorThiZon
Cortical Thickness of brain by Zones
CorThiZon is a Matlab toolbox. MRI 3D T1 images are treated to estimate cortical thickness by zones in native and normalized space. It uses a Laplace-based technique following brain segmentation. Results can be easily reported in Excel files for further statistical analysis. If you use this toolbox, please reference: ‘Early diagnostic of Alzheimer’s disease using cortical thickness: impact of cognitive reserve', Querbes O, Aubry F, Pariente J, Lotterie JA, Démonet JF, Duret V, Puel M, Berry I, Fort JC, Celsis P, Alzheimer’s Disease Neuroimaging Initiative, Brain, 2009 Aug, 132(Pt 8):2036-47 A footnote giving the link to: http://sourceforge.net/projects/corthizon/ will be appreciated. -
6
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 recall at a manageable number of proposals. ... -
7
PoisonTap
Exploits locked/password protected computers over USB
...It is best understood as a proof of concept for awareness, testing, and defensive hardening rather than a general-purpose utility. PoisonTap also illustrates why organizations need strong endpoint policies, USB restrictions, browser protections, and network segmentation. Its main value is educational: it makes invisible trust assumptions in desktop networking much easier to understand. -
8
W2MHS-DNN
Open Source White Matter Hyperintensities Segmentation Toolbox
Wisconsin White Matter Hyperintensity Segmentation [W2MHS] and Quantification Toolbox is an open source MatLab toolbox designed for detecting and quantifying White Matter Hyperintensities (WMH) in Alzheimer’s and aging related neurological disorders. WMHs arise as bright regions on T2- weighted FLAIR images. They reflect comorbid neural injury or cerebral vascular disease burden. -
9
ansvif
An advanced cross platform fuzzing framework suited to find code bugs.
...It supports many features, such as buffer size, randomization of the buffer size, random data injection, templates, and much more. The purpose of this project is to identify bugs in software, specifically bugs that can induce a segmentation fault under various conditions. This aids security researchers in writing buffer overflows, input validation vulnerabilities, as well as helping one audit code for general logic mistakes. -
Stop vibe-debugging.AppSignal's MCP server hands Claude, Cursor, or Zed your real errors, traces, and the deploy that shipped them. AI writes the fix; you review the diff.
-
10
cocolib / light field suite
CUDA library for continuous optimization and light field analysis
Library for continuous convex optimization in image analysis, together with a command line tool and Matlab interface. Implements several recent algorithms for inverse problems and image segmentation with total variation regularizers and vectorial multilabel transition costs. Also included is a suite for variational light field analysis, which ties into the HCI light field benchmark set and givens reference implementations for a number of our recently published algorithms. *** NOTE: documentation on the SourceForge page is outdated and not updated anymore, please visit http://cocolib.net *** -
11
mbFXWords
Analyze text. Diagonal read subject, predicate, obj. Search other pdf.
...For English, French and German files. JavaFX Application, runs with Oracle Java Runtime Environment version 8 that is including JavaFX. NLP extensions: - Divide sentences in subclauses: segmentation. - Divide plain text: subject, predicate, object. - Count words: stemming. - Search for similar content: pdf's. Gives out subject, predicate and object of sentences of pdf and plain text files. Provides comfortable GUI. Automatic language detection. -
12
Source code for the article: 'The Influence of Object Shape on the Convergence of Active Contour Models for Image Segmentation'. Images and .mat files are included to both run active contour models and create phase diagrams showing how object shape and choice of parameters affect the convergence of the models.
-
13
mzitu
Python crawler that downloads image galleries and analyzes titles
...It focuses on automating the collection of large sets of images by programmatically parsing page content and iterating through gallery entries. mzitu also includes a simple analysis script that processes downloaded folder names to generate statistics and visualizations. Using text segmentation and frequency analysis, the project can create a word cloud representing common keywords found in the dataset. This makes the repository both a scraping example and a small data analysis experiment built around the collected content. Overall, mzitu serves as a learning-oriented implementation of Python web scraping, data processing, and visualization techniques. -
14
DIGITS
Deep Learning GPU training system
The NVIDIA Deep Learning GPU Training System (DIGITS) puts the power of deep learning into the hands of engineers and data scientists. DIGITS can be used to rapidly train the highly accurate deep neural network (DNNs) for image classification, segmentation and object detection tasks. DIGITS simplifies common deep learning tasks such as managing data, designing and training neural networks on multi-GPU systems, monitoring performance in real-time with advanced visualizations, and selecting the best performing model from the results browser for deployment. DIGITS is completely interactive so that data scientists can focus on designing and training networks rather than programming and debugging. ... -
15
Convolutional Recurrent Neural Network
Convolutional Recurrent Neural Network (CRNN) for image-based sequence
...The architecture combines convolutional neural networks for extracting visual features from images with recurrent neural networks that model sequential dependencies in the extracted features. This hybrid approach allows the model to recognize sequences of characters directly from images without requiring explicit character segmentation. The implementation also integrates the Connectionist Temporal Classification (CTC) loss function, enabling end-to-end training of the model using labeled sequence data. CRNN has been widely used in computer vision tasks that require interpreting text embedded in images, such as reading street signs, documents, or natural scene text. -
16
pyhanlp
Chinese participle
...In practice, it serves as a bridge layer: Python calls are translated into the corresponding HanLP operations, so you can keep your application logic in Python while relying on HanLP’s implementations. It is especially useful when you need a pragmatic “get results quickly” NLP layer for segmentation, tagging, entity extraction, parsing, or keyword-style tasks rather than experimenting with model training from scratch. -
17
Telenor_User_Mobility
Code related to the collaboration between BTH and Telenor
In this project code written in different projects related to the mobility data BTH has acquired from Telenor in their collaboration. The paper "Trajectory Segmentation for a Recommendation Module of a Customer Relationship Management System" is published and can be found at https://www.researchgate.net/publication/316657841_Trajectory_Segmentation_for_a_Recommendation_Module_of_a_Customer_Relationship_Management_System The module for resource allocation is described in section 3 of the paper. ... -
18
House3D
A Realistic and Rich 3D Environment
...Each environment includes fully labeled 3D objects, allowing agents to perceive and interact with their surroundings through multiple sensory modalities including RGB images, depth maps, semantic segmentation masks, and top-down maps. The simulator is optimized for high-performance rendering, achieving thousands of frames per second to enable efficient large-scale training of RL agents. House3D has served as the foundation for several influential research projects such as RoomNav (for concept-based navigation) and Embodied Question Answering (EQA). -
19
uncaptcha
Defeating Google's audio reCaptcha with 85% accuracy
uncaptcha is an open-source proof-of-concept system designed to demonstrate vulnerabilities in Google’s audio reCAPTCHA challenges by automatically solving them using speech recognition techniques. The project uses browser automation to navigate to CAPTCHA challenges, extract audio files, and process them through multiple speech-to-text services. By combining outputs from several transcription engines, the system increases the likelihood of correctly identifying the spoken digits or phrases... -
20
Riot search
Go Open Source, Distributed, Simple and efficient Search Engine
...Support distributed index and search. Can be achieved distributed index and search. Look at Word segmentation rules. -
21
TOFSIMS
R/Bioconductor toolkit for mass spectrometry data
...For data exploration and dimensionality reduction, it includes multivariate methods common in the ToF-SIMS community: PCA (Principal Component Analysis), MCR (Multivariate Curve Resolution), MAF (Maximum Autocorrelation Factors), and MNF (Minimum Noise Fraction). It also interoperates with Bioconductor’s imaging stack (e.g. EBImage) so users can apply segmentation and image analysis operations on mass images. -
22
EasyPR
An easy, flexible, and accurate plate recognition project
...The system is designed to work in unconstrained environments, meaning it can handle images with varying lighting conditions, perspectives, and backgrounds. Its architecture includes multiple stages such as plate localization, character segmentation, and character classification to achieve accurate recognition results. -
23
-
24
A Generic Platform for Iris Recognition
A framework that allows iris recognition algorithms to be evaluated
This MATLAB based framework allows iris recognition algorithms from all four stages of the recognition process (segmentation, normalisation, encoding and matching) to be automatically evaluated and interchanged with other algorithms performing the same function. The algorithm for each stage can be selected from a list of available algorithms, with selection available for subfunctions as well. The selected algorithms can then be tested either manually against individual iris images, or automatically against a whole database of them. ... -
25
FATCALC-ImageJ is an ImageJ macro (fully automated) for unsupervised fat segmentation in magnetic resonance imaging. It was developed for GE T1 2-points Dixon sequences (fat only image). FATCALC independently evaluates the volumes of visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT).
