347 skills found · Page 2 of 12
balcilar / Comparison Of Disparity Estimation AlgorithmsImplementation of simple block matching, block matching with dynamic programming and Stereo Matching using Belief Propagation algorithm for stereo disparity estimation
jvkersch / TmtoolsPython bindings for the TM-align algorithm and code for protein structure comparison developed by Zhang et al.
darkobozidar / Cpu Vs Gpu SortingA comparison study between sequential sorting algorithms implemented in C++ and parallel sorting algorithms implemented in CUDA as part of the master's thesis.
harismuneer / Handwritten Digits Classification Using KNN Multiclass Perceptron SVM🏆 A Comparative Study on Handwritten Digits Recognition using Classifiers like K-Nearest Neighbours (K-NN), Multiclass Perceptron/Artificial Neural Network (ANN) and Support Vector Machine (SVM) discussing the pros and cons of each algorithm and providing the comparison results in terms of accuracy and efficiecy of each algorithm.
hsinnan75 / GSAlignGSAlign: an ultra-fast sequence alignment algorithm for intra-species genome comparison
zeux / NanosortFast comparison-based sort algorithm
alejandro-isaza / AIImageCompareLibrary of image comparison algorithms for iOS and OS X
libindic / SoundexSoundex Phonetic Code Algorithm Demo for Indian Languages. Supports all indian languages and English. Provides intra-indic string comparison
diffeo / Py NilsimsaLocality-sensitive hashing algorithm for text similarity comparisons
Krishna18062005 / Team Consistent Coders SolutionsThis repository contains solutions for various problems by Team Consistent Coders, showcasing multiple approaches and methods for each problem. It highlights different coding techniques, algorithms, and optimized solutions, making it a valuable resource for learning and comparison.
Shauqi / Attack And Anomaly Detection In IoT Sensors In IoT Sites Using Machine Learning ApproachesAttack and Anomaly detection in the Internet of Things (IoT) infrastructure is a rising concern in the domain of IoT. With the increased use of IoT infrastructure in every domain, threats and attacks in these infrastructures are also growing commensurately. Denial of Service, Data Type Probing, Malicious Control, Malicious Operation, Scan, Spying and Wrong Setup are such attacks and anomalies which can cause an IoT system failure. In this paper, performances of several machine learning models have been compared to predict attacks and anomalies on the IoT systems accurately. The machine learning (ML) algorithms that have been used here are Logistic Regression (LR), Support Vector Machine (SVM), Decision Tree (DT), Random Forest (RF), and Artificial Neural Network (ANN). The evaluation metrics used in the comparison of performance are accuracy, precision, recall, f1 score, and area under the Receiver Operating Characteristic Curve. The system obtained 99.4% test accuracy for Decision Tree, Random Forest, and ANN. Though these techniques have the same accuracy, other metrics prove that Random Forest performs comparatively better.
sobrinho / FoneticaBuscaBR algorithm which allow the comparison of words based on their phonetic likeness
mloskot / Spatial Index BenchmarkSimple non-academic performance comparison of available open source implementations of R-tree spatial index using linear, quadratic and R* balancing algorithms as well as bulk loading.
szandara / DEPRECATED 2DScanMatching SLAMSet of algorithms for 2D scan matching. Comparison of the state of the art.
decidedlyso / Merge Insertion SortA Clojure implementation of the comparison-efficient Merge Insertion Sort / Ford Johnson Algorithm
vasu-gondaliya / Cpu Scheduling Algorithms9 CPU Scheduling Algorithms with I/O Time, Gantt Chart, Context Switch, Time Log Animation, Timeline Chart, Comparison between all algorithms and more.
b0rxa / ScmampStatistical comparison of multiple algorithms
horita-yuya / DifferenceAlgorithmComparisonThere are many algorithm for getting difference between sequence A and B. Myers, Wu, Heckel Algorithm are discussed here.
lukebhan / PDEControlGymThis gym provides implementations of various PDEs for easy testing and comparison of data-driven and classical PDE control algorithms.
ssibb / PDF Diff ViewerPDF Diff Viewer, a side-by-side, visual highlight, sync-scroll, PDF comparer, written in Python. Open source, mostly powered by PyMuPDF and Tkinter. Optional support for git diff, for a better comparison algorithm.
