320 skills found · Page 3 of 11
luser / TracetreeA tool for capturing the execution of an entire process tree
bpowers / Mstatfine-grained, cgroup-based tool for profiling memory usage over time of a process tree
FredHucht / Pstreepstree shows the process listing as a tree
tuxarch / Pscirclehttps://gitlab.com/mildlyparallel/pscircle visualizes Linux processes in a form of radial tree.
ZSShen / C Common Data StructuresA fast and memory efficient C library to manipulate sequential containers, associative structures, and advanced string processing, such as tree map, hash map, and trie.
matheusgadelha / MRTNetCode for Multiresolution Tree Networks for 3D Point Cloud Processing (ECCV 2018)
joknarf / PgtreeUnix process hierachy tree for specific processes (mixed pgrep + pstree)
knaaga / Lidar Obstacle DetectionProcess LIDAR point cloud data for object detection. Implements RANSAC and Euclidean clustering with KD-Tree
cocoindex-io / Realtime Codebase Indexingbuild codebase index with tree-sitter. works with large codebases, and can be updated in near real-time with incremental processing - only reprocess what's changed.
Hartrik / Sand Game JsSand Game JS is a fast and powerful falling-sand game engine for desktop & mobile browsers. It allows players to experiment with various elements, such as sand, soil, water and fire. With grass and trees growing on soil, and other natural processes, it offers a unique experience.
abhiwalia15 / Python For Data Science And Machine Learning Bootcampprogram with Python, how to create amazing data visualizations, and how to use Machine Learning with Python! Here a just a few of the topics we will be learning: Programming with Python NumPy with Python Using pandas Data Frames to solve complex tasks Use pandas to handle Excel Files Web scraping with python Connect Python to SQL Use matplotlib and seaborn for data visualizations Use plotly for interactive visualizations Machine Learning with SciKit Learn, including: Linear Regression K Nearest Neighbors K Means Clustering Decision Trees Random Forests Natural Language Processing Neural Nets and Deep Learning Support Vector Machines and much, much more!
tejasprasad2008-afk / TraceTreeTraceTree - Runtime behavioral analysis tool that maps the process cascade of suspicious packages into a directed tree, catching supply chain attacks that install-time scanners miss.
keskival / Behavior Trees For Llm ChatbotsExample: Using Behavior Trees for structuring goal-driven LLM chatbot processes
sc1992sc / ProcessTreeNo description available
ACE-Responder / Ace ProctreeCreate a cool process tree like https://twitter.com/ACEResponder.
IdanAchituve / GP TreeGP-Tree: A Gaussian Process Classifier for Few-Shot Incremental Learning
shruti821 / Leaf Disease Detection Using Image ProcessingAgricultural productivity is something on which economy highly depends. This is the one of the reasons that disease detection in plants plays an important role in agriculture field, as having disease in plants are quite natural. If proper care is not taken in this area then it causes serious effects on plants and due to which respective product quality, quantity or productivity is affected. For instance a disease named little leaf disease is a hazardous disease found in pine trees in United States. Detection of plant disease through some automatic technique is beneficial as it reduces a large work of monitoring in big farms of crops, and at very early stage itself it detects the symptoms of diseases i.e. when they appear on plant leaves. This paper introduces an efficient approach to identify healthy and diseased or an infected leaf using image processing and machine learning techniques. Various diseases damage the chlorophyll of leaves and affect with brown or black marks on the leaf area. These can be detected using image prepossessing, image segmentation. Support Vector Machine (SVM) is one of the machine learning algorithms is used for classification. The Convolutional Neural Network (CNN) resulted in a improved accuracy of recognition compared to the SVM approach.
Miaplaza / Expression UtilsEfficient Processing, Compilation, and Execution of Expression Trees at Runtime
f-bader / XDRStoryParserVisualize Microsoft Defender XDR process trees and security events
LeadingIndiaAI / Fake News Detection Fake news is misinformation or manipulated news that is spread across the social media with an intention to damage a person, agency and organisation. Due to the dissemination of fake news, there is a need for computational methods to detect them. Fake news detection aims to help users to expose varieties of fabricated news. To achieve this goal, first we have taken the datasets which contains both fake and real news and conducted various experiments to organize fake news detector. We used natural processing, machine learning and deep learning techniques to classify the datasets. We yielded a comprehensive audit of detecting fake news by including fake news categorization, existing algorithms from machine learning techniques. In this project, we explored different machine learning models like Naïve Bayes, K nearest neighbors, decision tree, random forest and deep learning networks like Shallow Convolutional Neural Networks (CNN), Deep Convolutional Neural Network (VDCNN), Long Short-Term Memory Network (LSTM), Gated Recurrent Unit Network (GRU), Combination of Convolutional Neural Network with Long Short-Term Memory (CNN-LSTM) and Convolutional Neural Network with Gated Recurrent Unit (CNN-LSTM).
