350 skills found · Page 7 of 12
amberw68 / AFL EDGEAFL-EDGE is a tool facilitating parallel fuzzing with mutually-exclusive task distribution
cambridgeltl / Multi3wozThe official repository for Multi3WOZ: A Multilingual, Multi-Domain, Multi-Parallel Dataset for Training and Evaluating Culturally Adapted Task-Oriented Dialog Systems (TACL 2023)
ethicalhackingplayground / Shodan GrabberShodan-Grabber is a Node.js tool for scraping IP addresses and other information from Shodan's web interface. It utilizes Puppeteer for web scraping and handles rate limits by implementing retries with delays. The tool can run multiple scraping tasks in parallel and outputs the data to text files.
jainsee24 / Parallel Face DetectionImage segmentation is the process of dividing an image into multiple parts. It is typically used to identify objects or other relevant information in digital images. There are many ways to perform image segmentation including Thresholding methods, Color-based segmentation, Transform methods among many others. Alternately edge detection can be used for image segmentation and data extraction in areas such as image processing, computer vision, and machine vision. Image thresholding is a simple, yet effective, way of partitioning an image into a foreground and background. This image analysis technique is a type of image segmentation that isolates objects by converting grayscale images into binary images. Image thresholding is most effective in images with high levels of contrast. Otsu's method, named after Nobuyuki Otsu, is one such implementation of Image Thresholding which involves iterating through all the possible threshold values and calculating a measure of spread for the pixel levels each side of the threshold, i.e. the pixels that either fall in foreground or background. The aim is to find the threshold value where the sum of foreground and background spreads is at its minimum. Edge detection is an image processing technique for finding the boundaries of objects within images. It works by detecting discontinuities in brightness. An image can have horizontal, vertical or diagonal edges. The Sobel operator is used to detect two kinds of edges in an image by making use of a derivative mask, one for the horizontal edges and one for the vertical edges. 1. Introduction Face detection is a computer technology being used in a variety of applications that identifies human faces in digital images. Face detection also refers to the psychological process by which humans locate and attend to faces in a visual scene. Face detection can be regarded as a specific case of object-class detection. In object-class detection, the task is to find the locations and sizes of all objects in an image that belong to a given class. Examples include upper torsos, pedestrians, and cars. Face-detection algorithms focus on the detection of frontal human faces. It is analogous to image detection in which the image of a person is matched bit by bit. Image matches with the image stores in database. Any facial feature changes in the database will invalidate the matching process. 2. Needs/Problems There have been widely applied many researches related to face recognition system. The system is commonly used for video surveillance, human and computer interaction, robot navigation, and etc. Along with the utilization of the system, it leads to the need for a faster system response, such as robot navigation or application for public safety. A number of classification algorithms have been applied to face recognition system, but it still has a problem in terms of computing time. In this system, computing time of the classification or feature extraction is an important thing for further concern. To improve the algorithmic efficiency of face detection, we combine the eigenface method using Haar-like features to detect both of eyes and face, and Robert cross edge detector to locate the human face position. Robert Cross uses the integral image representation and simple rectangular features to eliminate the need of expensive calculation of multi-scale image pyramid. 3. Objectives Some techniques used in this application are 1. Eigen-face technique 2. KLT Algorithm 3. Parallel for loop in openmp 4. OpenCV for face detection. 5. Further uses of the techniques
aikar / ParataskJava Parallel Task Manager
Grademark / Task FarmerA simple multi-core task scheduler that works well with promises. Great for doing parallel data processing.
barryearles / Parallel Tasks Gradle PluginConcurrent execution of gradle tasks in the same module
wangchongjie / Multi EngineMulti-Engine is a Java framework for distributed parallel processing, whose kernel is Multi-Task.
emilbayes / Parallel QueueQueue for parallel tasks that can cancel and is destoryable
ssdeanx / Branch Thinking MCPBranch-Thinking MCP Tool A TypeScript-powered MCP server for managing parallel branches of thought, semantic cross-references, and persistent tasks. Features dynamic scoring, AI-generated insights, batch operations, and visual graph navigation for advanced agentic workflows.
Genuifx / Claude Code Env ManagerControl center for Claude Code & Codex — multi-model parallel sessions, Telegram remote control, scheduled cron tasks with push notifications, usage analytics, permission modes. CLI + native macOS desktop app.
cpp20120 / DagFlowA self-contained, minimal runtime for parallel task execution in C++20.
paulgavrikov / Parallel Matplotlib GridThis Python 3 module helps you speedup generation of subplots in pseudo-parallel mode using matplotlib and multiprocessing. This can be useful if you are dealing with expensive preprocessing or plotting tasks such as violin plots per subplot.
oxgeneral / ORCHOne CLI to orchestrate them all. Manage a team of AI agents executing tasks in parallel from your terminal.
betrcode / Ansible Run In ParallelLearn how to run Ansible tasks in parallel. Suitable when calling slow modules, such as cloud modules.
victor-gil-sepulveda / PySchedulerImplementation of a simple task scheduler. It can run taks in parallel.
0x1000000 / TaskAllIt simplifies execution of parallel tasks
BrunoMNDantas / TPL4JTask Parallel Library for Java
SFU-HiAccel / Pasta[FCCM 2023] PASTA: Programming and Automation Support for Scalable Task-Parallel HLS Programs on Modern Multi-Die FPGAs
xuzeyu91 / AI Agent ToolkitA powerful agent skill for orchestrating complex, multi-step tasks through distributed sub-agent execution. This skill decomposes complex user requests into atomic tasks and manages parallel execution through virtual agents, with optional integration with Claude CLI for true distributed processing.
