mosquito Computer Vision Project

Luis Augusto Silva

Updated 2 years ago

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Description

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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LICENSE

CC BY 4.0

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 2024-12-31 },
                            }