Flood detection from images using deep learning. Deep learning library KERAS was employed and MobileNet architecture was fine-tuned for image classification task.

Client project

Predicting the depth of water using deep convolutional neural network from flood image data.

Develop and train a CNN to determine depth of flooding from an image containing vehicles

Welcome to the YOLOv8 Human Detection Beginner's Repository – your entry point into the exciting world of object detection! This repository is tailored for beginners, providing a straightforward im…

YOLOv8 re-implementation for human detection using PyTorch

A dataset of images posted on Twitter with flood-related keywords, annotated according to their relevance regarding flood impact analysis.