my-thesis-by-model Instance Segmentation Dataset and Pre-Trained Model by aefnattanon

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Explore Dataset

Here are a few use cases for this project:

Utility Management: Use the "my-thesis-by-model" computer vision model to automate the process of identifying different meter classes (model 1, model 2) for utility companies managing water supply networks. This can enable more accurate asset tracking, streamlined maintenance processes, and improved resource management.
Water Consumption Monitoring: Integrate the "my-thesis-by-model" in smart city infrastructures to monitor water consumption at a granular level. This can help identify potential leaks or wastage patterns faster, leading to quick resolution of issues and more efficient water usage.
Residential and Commercial Billing: Employ the "my-thesis-by-model" to accurately identify meter classes in residential and commercial properties. This can enable utility companies to generate more accurate bills, reducing disputes and improving customer satisfaction.
Leak Detection and Prevention: Use the model to identify various meter classes and monitor readings remotely, allowing utility companies or property owners to detect unusual water consumption patterns, which could be indicative of leaks. This can lead to early identification and repair of issues, avoiding large-scale water damage or wastage.
Smart Home Integration: Incorporate the "my-thesis-by-model" into smart home systems, enabling homeowners to easily monitor their water consumption and receive alerts if any irregularities occur. This can promote more sustainable and responsible water usage and reduce overall consumption.

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.

YOLOv8

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.

YOLOv5

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:

@misc{
                            my-thesis-by-model_dataset,
                            title = { my-thesis-by-model Dataset },
                            type = { Open Source Dataset },
                            author = { aefnattanon },
                            howpublished = { \url{ https://universe.roboflow.com/aefnattanon/my-thesis-by-model } },
                            url = { https://universe.roboflow.com/aefnattanon/my-thesis-by-model },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { sep },
                            note = { visited on 2024-05-04 },
                            }