Aedes Mosquitos Dataset

Dataset Description

• Total Images: 4,120
• Species: Aedes aegypti, Aedes albopictus
• Image Resolution: Varies (High Quality)
• Format: JPEG
• Labels: Species name per image

Usage

Ideal for research and development of machine learning models, this dataset supports training and validation of deep learning frameworks like convolutional neural networks (CNNs) for mosquito species classification.

Research Context

The Aedes mosquitoes dataset, specifically targeting Aedes aegypti and Aedes albopictus, serves as a crucial resource for advancing research in public health and vector-borne disease control. These two species are notorious vectors of diseases such as dengue, Zika, chikungunya, and yellow fever, making their accurate identification essential for timely intervention and disease mitigation strategies.

The dataset underpinned research titled “Implementation of a Deep Learning Model for Automated Classification of Aedes Aegypti and Aedes Albopictus in Real Time,” which highlights the potential of artificial intelligence and deep learning in automating the classification of these species.