Search Results for "detection"
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Showing 417 open source projects for "detection"
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Python Outlier Detection
A Python toolbox for scalable outlier detection
PyOD is a comprehensive and scalable Python toolkit for detecting outlying objects in multivariate data. This exciting yet challenging field is commonly referred as outlier detection or anomaly detection. PyOD includes more than 30 detection algorithms, from classical LOF (SIGMOD 2000) to the latest COPOD (ICDM 2020) and SUOD (MLSys 2021). Since 2017, PyOD [AZNL19] has been successfully used in numerous academic researches and commercial products [AZHC+21, AZNHL19]. PyOD has multiple neural network-based models, e.g., AutoEncoders, which are implemented in both PyTorch and Tensorflow. ... -
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Awesome Fraud Detection Research Papers
A curated list of data mining papers about fraud detection
A curated list of data mining papers about fraud detection from several conferences. -
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DeltaForce-OBS-Locker
Delta Action OBS Lock Plugin
...It is most appropriate for studying visual detection pipelines, UI capture, and input-simulation concepts in controlled environments. -
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YOLOv9
Learning What You Want to Learn Using Programmable Gradient Info
YOLOv9 is the official implementation of the paper “YOLOv9: Learning What You Want to Learn Using Programmable Gradient Information.” It is a modern object detection repository focused on improving how deep networks preserve useful information during training. The project introduces Programmable Gradient Information and the GELAN architecture to improve gradient flow, parameter efficiency, and train-from-scratch performance. It provides scripts and model assets for training, testing, and running inference on detection tasks. ... -
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Anomalib
An anomaly detection library comprising state-of-the-art algorithms
Anomalib is an open-source deep learning library focused on anomaly detection and localization tasks, collecting state-of-the-art algorithms and tools under one modular framework. It provides implementations of leading anomaly detection methods drawn from current research, as well as a full set of utilities for training, evaluating, benchmarking, and deploying these models on both public and private datasets. -
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ML.NET
Open source and cross-platform machine learning framework for .NET
...ML.NET has been designed as an extensible platform so that you can consume other popular ML frameworks (TensorFlow, ONNX, Infer.NET, and more) and have access to even more machine learning scenarios, like image classification, object detection, and more. -
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KubeClarity
KubeClarity is a tool for detection and management of vulnerabilities
KubeClarity is a tool for detection and management of Software Bill Of Materials (SBOM) and vulnerabilities of container images and filesystems. It scans both runtime K8s clusters and CI/CD pipelines for enhanced software supply chain security. Effective vulnerability scanning requires an accurate Software Bill Of Materials (SBOM) detection. KubeClarity includes a CLI that can be run locally and especially useful for CI/CD pipelines. -
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satellite-image-deep-learning
Resources for deep learning with satellite & aerial imagery
This page lists resources for performing deep learning on satellite imagery. To a lesser extent classical Machine learning (e.g. random forests) are also discussed, as are classical image processing techniques. Note there is a huge volume of academic literature published on these topics, and this repository does not seek to index them all but rather list approachable resources with published code that will benefit both the research and developer communities. If you find this work useful... -
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Random Cut Forest by AWS
An implementation of the Random Cut Forest data structure
This repository contains implementations of the Random Cut Forest (RCF) probabilistic data structure. RCFs were originally developed at Amazon to use in a nonparametric anomaly detection algorithm for streaming data. Later new algorithms based on RCFs were developed for density estimation, imputation, and forecasting. The different directories correspond to equivalent implementations in different languages, and bindings to to those base implementations, using language-specific features for greater flexibility of use. -
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Albumentations
Fast image augmentation library and an easy-to-use wrapper
...Albumentations efficiently implements a rich variety of image transform operations that are optimized for performance, and does so while providing a concise, yet powerful image augmentation interface for different computer vision tasks, including object classification, segmentation, and detection. Albumentations supports different computer vision tasks such as classification, semantic segmentation, instance segmentation, object detection, and pose estimation. Albumentations works well with data from different domains: photos, medical images, satellite imagery, manufacturing and industrial applications, Generative Adversarial Networks. ... -
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dlib
Toolkit for making machine learning and data analysis applications
Dlib is a modern C++ toolkit containing machine learning algorithms and tools for creating complex software in C++ to solve real world problems. It is used in both industry and academia in a wide range of domains including robotics, embedded devices, mobile phones, and large high performance computing environments. Dlib's open source licensing allows you to use it in any application, free of charge. Good unit test coverage, the ratio of unit test lines of code to library lines of code is... -
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Anthropic Cybersecurity Skills
754 structured cybersecurity skills for AI agents
Anthropic Cybersecurity Skills is a collection of structured prompts, tools, and workflows designed to enhance the cybersecurity capabilities of AI systems. It focuses on defining reusable “skills” that guide AI models in performing tasks such as vulnerability analysis, threat detection, and security auditing. The project is intended for experimentation and development of AI-assisted cybersecurity workflows, providing templates that can be adapted to different environments. It emphasizes structured interaction patterns, ensuring that outputs are consistent and actionable. The repository also encourages modularity, allowing individual skills to be combined into larger security pipelines. ... -
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trackers
Multi-object tracking algorithms
...Trackers is built for flexibility and benchmarking, allowing users to evaluate performance using standard multi-object tracking metrics and compare algorithms easily. Its architecture emphasizes interoperability so developers can combine their preferred detection models with different trackers without rewriting core logic. -
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Mobile Detect
Mobile_Detect is a lightweight PHP class for detecting mobile devices
...Because it is pattern-driven and optimized for fast matching, it adds minimal runtime overhead to request handling. By abstracting away the complexity of UA sniffing, Mobile-Detect helps teams gracefully support multi-device clients without duplicating detection logic. -
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Highlight.js
JavaScript syntax highlighter with language auto-detection
Highlight.js is a syntax highlighter written in JavaScript. It works in the browser as well as on the server. It can work with pretty much any markup, doesn’t depend on any other frameworks, and has automatic language detection. Highlight.js supports over 180 languages in the core library. There are also 3rd party language definitions available to support even more languages. We strongly recommend <pre><code> wrapping for code blocks. It's quite semantic and "just works" out of the box with zero fiddling. It is possible to use other HTML elements (or combos), but you may need to pay special attention to preserving linebreaks. ... -
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Immutable.js
Immutable collections for JavaScript
...Immutable data is unchangeable once created, which makes application development so much simpler. There’s no defensive copying, and you get advanced memoization and change detection techniques with simple logic. Persistent data gives you a mutative API, one that doesn’t update data in-place but always produces new and updated data. The data structures that Immutable.js provides include List, Stack, Map, OrderedMap, Set and more. These structures are highly efficient on modern JavaScript VMs, and minimize the need to cache or copy data. -
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Impeccable
The design language that makes your AI harness better at design
...It can be installed across several AI coding environments, including Claude Code, Cursor, Codex, Gemini CLI, GitHub Copilot, and others. Impeccable also includes deterministic anti-pattern detection through a CLI and browser extension without requiring an API key. It is most useful for developers and designers who want AI-generated interfaces to feel more polished, intentional, and product-aware. -
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Machine Learning Octave
MatLab/Octave examples of popular machine learning algorithms
...The author’s goal is to help users understand how each algorithm works “from scratch,” avoiding black-box library calls. Code written so as to expose and comment on mathematical steps. The repository includes clustering, regression, classification, neural networks, anomaly detection, and other standard ML topics. Does not rely heavily on specialized toolboxes or library shortcuts. -
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Exclusively Dark Image Dataset
ExDARK dataset is the largest collection of low-light images
...It contains 7,363 images captured across ten different low-light scenarios, ranging from extremely dark environments to twilight. Each image is annotated with both image-level labels and object-level bounding boxes for 12 object categories, making it suitable for detection and classification tasks. The dataset was created to address the lack of large-scale low-light datasets available for research in object detection, recognition, and enhancement. It has been widely used in studies of low-light image enhancement, deep learning approaches, and domain adaptation for vision models. Researchers can also explore its associated source code for low-light image enhancement tasks, making it an essential resource for advancing work in night-time and low-light visual recognition. -
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RA.Aid
Develop software autonomously
RA.Aid is an AI-powered assistant designed to enhance the efficiency of software development workflows. It integrates seamlessly with various development environments, providing intelligent code suggestions, automated documentation generation, and real-time error detection. By leveraging advanced machine learning models, RA.Aid aims to reduce development time and improve code quality. -
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Maltrail
Malicious traffic detection system
Maltrail is a malicious traffic detection system, utilizing publicly available (black)lists containing malicious and/or generally suspicious trails, along with static trails compiled from various AV reports and custom user-defined lists, where trail can be anything from domain name, URL, IP address (e.g. 185.130.5.231 for the known attacker) or HTTP User-Agent header value (e.g. sqlmap for automatic SQL injection and database takeover tool). -
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ripgrep
Regex pattern directory search tool that respects your .gitignore
...By default, ripgrep will ignore your .gitignore and skip hidden files or directories and binary files automatically. ripgrep has first class support on Windows, macOS and Linux, with binary downloads available for every release. ripgrep is similar to other popular search tools like The Silver Searcher, ack and grep. ripgrep supports arbitrary input preprocessing filters which could be PDF text extraction, less supported decompression, decrypting, automatic encoding detection and so on. In other words, use ripgrep if you like speed, filtering by default, fewer bugs and Unicode support. -
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leak-check
Personal Information “Leakage ” Detection Interface
leak-check is a utility designed to help developers detect memory leaks and resource mismanagement in applications. It provides tools to monitor allocations, track usage patterns, and identify potential leaks during runtime. The project focuses on improving application stability by highlighting inefficiencies in memory handling. It can be integrated into development workflows to catch issues early in the debugging process. leak-check is particularly useful in performance-critical... -
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BizHawk
BizHawk is a multi-system emulator written in C#
A multi-system emulator written in C#. As well as quality-of-life features for casual players, it also has recording/playback and debugging tools, making it the first choice for TASers (Tool-Assisted Speedrunners). Screenshotting and recording audio + video to file. Firmware management, input, framerate, and more in a HUD over the game. Rebindable hotkeys for controlling the frontend (keyboard+mouse+gamepad). A comprehensive input mapper for the emulated gamepads and other peripherals.... -
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Deequ
Deequ is a library built on top of Apache Spark
...It can scale to large datasets (billions of rows) by translating those data checks into Spark jobs. Deequ supports advanced features like a metrics repository for storing computed statistics over time, anomaly detection of data quality metrics, and the suggestion of likely constraints automatically for new datasets. It also includes a little domain-specific language called DQDL (Data Quality Definition Language) which allows declarative specification of quality rules. Users typically run Deequ before feeding data downstream (to ML pipelines, analytics, or production systems), enabling early detection and isolation of data errors. ...
