Ateneo de Zamboanga University

Thesis YoloV5

Object Detection

Thesis YoloV5 Computer Vision Project

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Explore Dataset

Here are a few use cases for this project:

  1. Horror Movie Content Filtering: Thesis YoloV5 can be used by streaming platforms and content providers to identify and categorize horror movies based on the type of horror imagery present, offering tailored content recommendations to users based on their preferred horror subgenres.

  2. Video Game Scene Classification: Game developers can use Thesis YoloV5 to analyze video game scenes in horror games, enabling more immersive and dynamic gameplay experiences by adapting game environments, NPC interactions, or difficulty levels according to the detected horror elements.

  3. Content Moderation for Online Communities: Online forums, social media platforms, and image sharing sites can utilize Thesis YoloV5 to ensure that users adhere to content policies, automatically moderating and flagging inappropriate horror imagery to maintain a safe and inclusive online community.

  4. Augmented Reality Experiences: Thesis YoloV5 can be integrated into AR applications to generate interactive and engaging horror-themed experiences for entertainment, education, or marketing purposes. Users could interact with AI-generated horror characters, solve puzzles based on detected horror elements, or enjoy immersive and personalized storytelling experiences.

  5. Horror-centric Art and Design: Artists, graphic designers, and filmmakers can use Thesis YoloV5 to analyze and reference horror imagery for creating unique visual styles, mood boards, and thematic concepts for art, design projects, or marketing campaigns centered around horror themes.

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.


This project has a YOLOv8 model checkpoint available for inference with Roboflow Deploy. YOLOv8 is a new state-of-the-art real-time object detection model.


This project has a YOLOv5 model checkpoint available for inference with Roboflow Deploy. YOLOv5 is a proven and tested, production ready, state-of-the-art real-time object detection model.

Cite This Project

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

                            title = { Thesis YoloV5 Dataset },
                            type = { Open Source Dataset },
                            author = { Ateneo de Zamboanga University },
                            howpublished = { \url{ } },
                            url = { },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { aug },
                            note = { visited on 2024-02-21 },

Connect Your Model With Program Logic

Find utilities and guides to help you start using the Thesis YoloV5 project in your project.

Last Updated

7 months ago

Project Type

Object Detection




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