MosquitoFusion: A Multiclass Dataset for Real-Time Detection of
  Mosquitoes, Swarms, and Breeding Sites Using Deep Learning
Md. Faiyaz Abdullah Sayeedi Fahim Hafiz Md Ashiqur Rahman
In this paper, we present an integrated approach to real-time mosquito
detection using our multiclass dataset (MosquitoFusion) containing 1204 diverse
images and leverage cutting-edge technologies, specifically computer vision, to
automate the identification of Mosquitoes, Swarms, and Breeding Sites. The
pre-trained YOLOv8 model, trained on this dataset, achieved a mean Average
Precision (mAP@50) of 57.1%, with precision at 73.4% and recall at 50.5%. The
integration of Geographic Information Systems (GIS) further enriches the depth
of our analysis, providing valuable insights into spatial patterns. The dataset
and code are available at https://github.com/faiyazabdullah/MosquitoFusion.