Roboflow Universe AI lifeguard unwanted behavior detection

unwanted behavior detection Computer Vision Project

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The unwanted behavior detection: The unwanted behavior detection model is designed to identify and flag behaviors in aquatic environments that pose risks or are deemed inappropriate, such as running or fighting. This model uses computer vision techniques to monitor and analyze movements and interactions around water bodies, enhancing safety measures and intervention capabilities.

Project Overview

Model Architecture: coco Developer: Ahmad Zidan Dataset The dataset used for training the coco model includes a diverse set of images depicting various scenarios related to water activities. Images are labeled into two classes: "wanted" and "unwated." contact: Email: a7madzidan001@gmail.com Linkedin: www.linkedin.com/in/ahmad-zidan-165259214

Trained Model API

This project has a trained model available that you can try in your browser and use to get predictions via our Hosted Inference API and other deployment methods.

Cite This Project

If you use this dataset in a research paper, please cite it using the following BibTeX:

@misc{
                            unwanted-behavior-detection_dataset,
                            title = { unwanted behavior detection   Dataset },
                            type = { Open Source Dataset },
                            author = { AI lifeguard },
                            howpublished = { \url{ https://universe.roboflow.com/ai-lifeguard-6qzmf/unwanted-behavior-detection } },
                            url = { https://universe.roboflow.com/ai-lifeguard-6qzmf/unwanted-behavior-detection },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2024 },
                            month = { may },
                            note = { visited on 2024-05-05 },
                            }