1,602 skills found · Page 16 of 54
nathanrooy / Spatial AnalysisA collection of algorithms I use for the analysis of geospatial data. Written in C, wrapped in Python.
saivittalb / Branch Prediction Programming🎞 Implementation of several Branch Prediction algorithms and analysis on their effectiveness on real-world program traces.
farzadasgari / ProadvProADV is a Python package designed for efficient processing and analysis of acoustic Doppler velocimeter (ADV) data. It offers advanced cleaning algorithms for robust despiking and noise removal, comprehensive statistical functions for calculating essential measures, and further analysis capabilities.
fish2000 / LibsiftfastMy fork of zerofrog's fast SIFT C++ reimplementation of Bill Lowe's original smash-hit image-analysis algorithm.
Solrikk / CriptoWhisperTradeWhisperer is a sophisticated cryptocurrency trading bot that leverages advanced Reinforcement Learning techniques, specifically the Proximal Policy Optimization (PPO) algorithm, to navigate the complex world of crypto markets. Built with a focus on adaptability and risk management, this bot combines technical analysis with machine learning.
zyh1996saa / Power Flow Calculation Based On A Physics Informed Graph Neural NetworkThis is an example in the IEEE 39-bus system to illustrate how the algorithm proposed in the paper "Cascading Failure Analysis Based on a Physics-Informed Graph Neural Network" is implemented.
leeeric9527 / Data Mining R利用R语言编写的数据挖掘大作业。着重分析朴素贝叶斯判别分析算法、 AdaBoost 算法以及随机森林算法在口红销量预测中的效果， 并在随机森林算法中进行模型优化。Using R language data mining big homework. The effects of Naive Bayesian Discriminant Analysis (Naive Bayesian Discriminant Analysis), AdaBoost and Random Forest Algorithms on lipstick sales forecasting were analyzed, and the model was optimized in Random Forest Algorithms.
evelinesurbakti / Automated Keywords Extraction Of Data Analyst Job Descriptions From Indeed Using NLPScraped job description and leveraged the concepts of Natural Language Processing (NLP) and GloVe Algorithm to extract the keywords through data and performed analysis. Presenting the vital keywords from data analyst job summary from the Indeed website..
Shaobinggao / Multi Illuminant Based Color ConstancyCombining bottom-up and top-down visual mechanisms for color constancy under varying illumination. This repository contains the datasets and codes published for color constancy under varying illmunations. -----------COPYRIGHT NOTICE STARTS WITH THIS LINE------------ Copyright (c) 2019 All rights reserved. This doucuments are a rough version for summarizing the results and codes in publication [1], which is available only for research purpose. We preserve the rights to further correct and update the data. This dataset contains three datasets for color constancy under varying illuminations, which are used in publication [1]. real-world dataset with multi-illuminant: the real-world dataset contains 37 images captured under vairous non-uniform light sources. synthetic dataset with multi-illuminant: the dataset with the synthetic multiple illuminants contains 100 images. MCC-BU+TD: This dataset contains results of multiple MCC algorithms on several real-world images taken from the web, which could be easily used and compared in any research publications. More information please refer to readme.txt in each folder. If you use this dataset for the evaluation of your approach and producing the results, please cite our work as follows: [1] S. Gao, Y. Ren, M. Zhang and Y. Li, "Combining bottom-up and top-down visual mechanisms for color constancy under varying illumination," in IEEE Transactions on Image Processing. doi: 10.1109/TIP.2019.2908783 [2] X.-S. Zhang, S.-B. Gao, R.-X. Li, X.-Y. Du, C.-Y. Li, and Y.-J. Li, “A retinal mechanism inspired color constancy model,” IEEE Transactions on Image Processing, vol. 25, no. 3, pp. 1219–1232, 2016. [3] K.-F. Yang, S.-B. Gao, Y.-J. Li, and Y. Li, “Efficient illuminant estimation for color constancy using grey pixels,” in Proceedings of the IEEE conference on computer vision and pattern recognition, 2015, pp. 2254–2263. [4] Gao, S. B., Yang, K. F., Li, C. Y., & Li, Y. J. (2015). Color constancy using double-opponency. IEEE transactions on pattern analysis and machine intelligence, 37(10), 1973-1985. Any questions and comments are welcome to gaoshaobing@scu.edu.cn
Dammonoit / Student Performance Analysis Using Big DataThis project analyses and correlates student performance with different attributes. Then at last, it determines most suitable algorithm from bunch of them.
lkorth / Botnet DetectionA network analysis algorithm for detecting bots on large networks.
petabi / Petal DecompositionMatrix decomposition algorithms including PCA (principal component analysis) and ICA (independent component analysis)
pmla / Polyhedral Template MatchingPolyhedral Template Matching algorithm for analysis of molecular dynamics simulation data
JEFworks / Tsne OnlineOnline web tool for t-SNE analysis and interactive exploration of algorithm parameters
pav-code / MDoppler ThesisHuman activity classification using simulated micro-Dopplers and time-frequency analysis in conjunction with machine learning algorithms: a comparative study for automotive use. Code and tools.
DIAGNijmegen / OpencxrA collection of open-source algorithms for chest X-ray analysis
glennga / HokuThis repository holds research toward analysis of lost-in-space star identification algorithms in C++.
konstantd / RF Array Signal ProcessingThe project is related to BeamForming and Direction of Arrival (DoA) algorithms and its scope is the analysis and understanding of such techniques.
gssci / NGM Sentiment AnalysisImplementation of Neural Graph Machine inspired by the paper [2017 - Bui, Ravi Ramavajjala - Neural Graph Machines: Learning Neural Networks Using Graphs] (https://arxiv.org/abs/1703.04818) for binary Sentiment Analysis using the Large Movie Review Dataset. This is an optional project for a class in Advanced Algorithms and Parallel Programming
vansh-121 / Multi Agent AI Finance AssistantThe Multi-Agent AI Finance Assistant is an open-source platform designed to provide intelligent financial analysis and decision-making support using a multi-agent AI framework. Leveraging large language models (LLMs) and advanced financial algorithms.
