Brain tumour detector built with YOLOv8 model.

[NeurIPS 2022 Spotlight] RLIP: Relational Language-Image Pre-training and a series of other methods to solve HOI detection and Scene Graph Generation.

This is a Face detection using Haar cascades project .Here use machine learning based approach where a cascade function is trained with a set of input data. OpenCV already contains many pre-trained classifiers for face, eyes, etc.here we will be using the face classifier.

Underwater object detection for marine research.

Detecting features on pictures using YOLO, Panoramax & OpenStreetMap. MOVED TO https://gitlab.com/panoramax/docs/detection-tutorial

Computer vision using YOLOV8 for logo recognition and identification

Phishing website detection using ML Algorithms

This project includes a python script that creates graphs by reading data from CSV files of models trained with YOLO.

Bounding Box Regression with Uncertainty for Accurate Object Detection (CVPR'19)

This repo copy from https://peterwang512.github.io/CNNDetection/

A smart surveillance camera system capable of detecting accidents involving large vehicles and automating the ambulance dispatch process.

Emotion based music recommendation system

Potato leaf disease detection using a CNN

Implementation of YOLOv8 for detection of Baybayin characters, an ancient script from the Philippines.

This repository was made to save and old project from Preparatory/Highschool in which I made a Facemask detector in python using a page called Teachable Machine which creates you a Machine Learning model by just passing it images.

This repository delves into predicting customer interest in vehicle insurance amongst existing health insurance holders. It explores historical data (past year) to build a model that identifies potential customers for vehicle insurance cross-selling opportunities.

Aplicación de estrategias de deep-learning para la detección de animales en imágenes de fototrampeo

Tuberculosis fake news detection

Our project tackles the crucial task of detecting coffee leaf diseases like Rust, Cercospora, and Phoma, endangering Kenya's coffee farms. Using state-of-the-art technology and Arabica coffee leaf image data, our CNN models deliver impressive accuracy, providing farmers with early disease detection to protect their livelihoods.