Focus stacking code

Implementation of the paper Identifying Mislabeled Data using the Area Under the Margin Ranking: https://arxiv.org/pdf/2001.10528v2.pdf

An online examination monitoring system employing YOLOv8, along with various other deep learning and machine learning approaches, centered around computer vision.

A Java program that removes ambient noise from an audio file

A collection of algorithms for detecting and handling label noise

Code basis for the paper "Real-time Noise Source Estimation of a Camera System from an Image and Metadata" (Advanced Intelligent Systems, 2024)

Data Science

Framework for P300 wave detection and noise-based cyberattacks in Brain-Computer Interfaces - Enrique Tomás Martínez Beltrán

Implements the CAIRAD techique for detecting noisy values in a dataset for Weka

Synthesis Image Noise Detection on Distributed Data : A web app to collect data on noise detection by humans on images.

Trabalhos desenvolvidos para a disciplina Sistemas de Recomendação do curso de Ciência da Computação da UFRRJ. Estes trabalhos realizam uma análise de técnicas de recomendação que utilizam filtragem colaborativa.

A Density-based spatial clustering of applications with noise implementation to C-languange

FonGuard turns your phone into a sentinel watching out for intruders and reporting any suspect motion, noise or vibration in real time.

An implementation of OPTICS Algorithm

Smart browser-based sound masking that adapts to your environment. Features adaptive noise detection, natural sound recordings, sleep timers, and saved presets. No installation required - works 100% in your browser. Privacy-focused: all processing happens locally, no data collection.

An implemantion of LOF Algorithm to C-lang.

Smart safety helmet for large scale construction sites

Environment noise grading and using it to manage deep learning models for higher accuracy classification/detection.

micko, the unapologetic microphone volume monitor.

Personal implementation of the paper "A two-stage ensemble method for the detection of class-label noise"