8 repository-uri
Tracks connectivity information across grid states using plug-based methods to solve path and tiling problems.
Distinct from Algorithmic Problem Solving: Focuses on plug-based DP, distinct from general algorithmic problem solving.
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This project is a curated educational resource and solution repository for algorithmic challenges, specifically focused on LeetCode problems. It serves as a technical reference for common data structures and algorithmic patterns, providing verified code implementations across multiple programming languages alongside detailed logic and complexity analysis. The repository functions as a comprehensive study guide for competitive programming and technical interview preparation. It includes specialized learning tools such as an Anki flashcard dataset for spaced repetition and a browser extension t
Implements depth-first search to identify and count connected components within 2D grids.
This project is a comprehensive, community-maintained knowledge base and toolkit designed for competitive programming. It serves as a centralized repository for algorithmic theory, data structures, and mathematical techniques, providing a structured reference for informatics and collegiate programming competitions. The project distinguishes itself by integrating educational content with a robust suite of automation utilities. It provides a complete workflow for competitive programming, including tools for automated test case generation, solution verification, and direct interaction with onlin
Implements plug-based dynamic programming to solve complex grid connectivity and tiling problems.
LogicStack-LeetCode is a curated repository of solved algorithm problems and data structure implementations, primarily drawn from the LeetCode platform. Its core identity is a structured collection of solutions designed to support technical interview preparation and competitive programming practice, with each solution accompanied by complexity analyses to help engineers understand performance trade-offs. The repository distinguishes itself through its breadth of coverage across fundamental algorithmic patterns and data structures. It includes implementations for array manipulation, string pro
Solves grid distance and state propagation problems using multi-source BFS.
GoCV is a computer vision library and Go language binding for OpenCV. It serves as an image processing toolkit and deep learning inference engine, providing programmatic access to a wide range of algorithms for image manipulation, object detection, and video analysis. The project differentiates itself through high-performance native bindings and hardware acceleration. It utilizes a foreign function interface to map Go calls to C++ functions and includes a hardware-agnostic backend dispatch to route neural network tasks to computation engines such as CUDA and OpenVINO. The library covers a br
Labels and counts connected regions of pixels to separate distinct objects in binary images.
OpenCVSharp is a .NET library that wraps native OpenCV functions, providing C# developers with access to OpenCV's computer vision capabilities through an API that mirrors the native C/C++ style. It serves as a managed wrapper for image processing, feature detection, object detection, and image manipulation tasks, while also handling automatic disposal of unmanaged OpenCV resources like Mat objects to prevent memory leaks in .NET applications. The library enables keypoint detection and descriptor extraction using algorithms such as AKAZE, BRISK, or FAST, with brute-force or FLANN-based matchin
Labels connected regions of foreground pixels in binary images and returns blob properties.
SwiftOCR este o bibliotecă nativă Swift concepută pentru extragerea textului și a caracterelor alfanumerice din imagini. Acesta funcționează ca un recunoscător de text cu rețea neuronală care identifică caracterele și șirurile de caractere din datele vizuale. Biblioteca include un antrenor de modele OCR personalizat și instrumente pentru recunoașterea fonturilor personalizate. Aceste capabilități permit generarea de rețele neuronale specializate adaptate pentru fonturi și seturi de caractere specifice pentru a îmbunătăți acuratețea recunoașterii. Sistemul utilizează etichetarea componentelor conectate pentru a identifica regiunile individuale ale caracterelor și utilizează procesarea imaginilor pentru a converti codurile alfanumerice scurte în text digital.
Employs connected-component identification to locate individual character blobs in images.
Memgraph is an in-memory, distributed graph database designed for high-performance labeled property graph management. It utilizes a Cypher query engine for declarative data retrieval and manipulation, providing a scalable knowledge graph backend that integrates vector search and graph traversals. The system distinguishes itself as a real-time graph analytics platform, employing native C++ and CUDA implementations to execute complex network analysis and dynamic community detection on streaming data. It provides specialized support for AI integration, including GraphRAG capabilities, the constr
The product groups nodes into separate components where no edges exist between different groups.
This project is a comprehensive repository of fundamental computer science algorithms and data structures designed as a reference for academic study, technical interview preparation, and competitive programming. It provides standardized implementations of core computational strategies, serving as an educational resource for developers to master software engineering fundamentals and algorithmic problem-solving. The collection distinguishes itself through a multi-language approach, offering cross-language solutions for complex tasks ranging from graph traversal and dynamic programming to bitwis
Implements algorithms for identifying and counting contiguous regions of identical values in a grid.