Roboflow Universe Luis Augusto Silva mosquito

mosquito Computer Vision Project

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Automatic Detection of Mosquito Breeding Grounds using YOLOv7 and Transformer Prediction Head. This project implements a deep learning algorithm for the automatic detection of mosquito breeding grounds in images and videos. The algorithm is based on a pre-trained YOLOv7 model with a Transformer Prediction Head, fine-tuned on a custom dataset of mosquito breeding sites. The dataset was created from a subset of the SMT Lab (UFRJ) dataset and includes 5,094 annotated images. The algorithm can detect mosquito breeding sites in real-world scenarios with various lighting and weather conditions, making it a useful tool for public health officials and researchers. This project was developed as part of a challenge for a conference on the detection of mosquito breeding grounds.

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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{
                            mosquito-suh0p_dataset,
                            title = { mosquito Dataset },
                            type = { Open Source Dataset },
                            author = { Luis Augusto Silva },
                            howpublished = { \url{ https://universe.roboflow.com/luis-augusto-silva-bq4bv/mosquito-suh0p } },
                            url = { https://universe.roboflow.com/luis-augusto-silva-bq4bv/mosquito-suh0p },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { apr },
                            note = { visited on 2024-05-17 },
                            }