Multi-target tracker based on cost computation.
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Updated
Jun 20, 2017 - C++
Multi-target tracker based on cost computation.
A collection of interesting, memorable, and well... mundane projects developed for and during my bachellor's and master's degree at PUPR(San Juan, PR) and JHU(Baltimore, MD), respectively.
📌 1. Compute the Mahalanobis distance from a centroid for a given set of training points. 2. Implement Radial Basis function (RBF) Gaussian Kernel Perceptron. 3. Implement a k-nearest neighbor (kNN) classifier
Fisher Linear Discriminant Analysis (FLD) Application
Finding Covariance Matrix, Correlation Coefficient, Euclidean and Mahalanobis Distance
Contains the codes for Extended Histogram of Gradients for object recognition developed by me during my PhD studies.
Our solution for Fujitsu LOD4ALL 2016 hackathon
A credit card fraud detection algorithm.
An example of a minimum distance classificator doing a comparison between using Mahalanobis distance and Euclidean distance.
Plugins to Phy1 - additional features to Phy
Graph-based image anomaly detection algorithm leveraging on the Graph Fourier Transform
统计分析课程实验作业/包含《统计分析方法》中因子分析,主成分分析,Kmeans聚类等典型算法的手写实现
Case-based Reasoning (CBR) System
This Project is detect outliers in sensor networks. We are using ISSNIP Single hop dataset for this.
A Data Mining Streamlit Application for Astrophysical Prediction using Random Forest Classification in Python
An implementation of a density based outlier detection method - the Local Outlier Factor Technique, to find frauds in credit card transactions. For detecting both local and global outliers.
The code for large margin metric learning for nearest neighbor classification and its acceleration using triplet mining and stratified sampling
Application of Multivariate Statistics on customer’ habits features to obtain a Customer segmentation of a wholesale shop.
These projects were carried out as part of the MATH2021-1 High-dimensional data analysis course of the ULiege.
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