Pink-Eggs Dataset V1: A Step Toward Invasive Species Management Using Deep Learning Embedded Solutions

TL;DR

This paper presents Pink-Eggs Dataset V1, a collection of annotated images of pink eggs potentially from invasive Pomacea canaliculata, aiming to support deep learning research for invasive species management.

Contribution

The paper introduces a new annotated image dataset for Pomacea canaliculata eggs to facilitate deep learning-based invasive species analysis.

Findings

Dataset contains images with bounding box annotations.

Supports research on invasive species detection.

Highlights need for species identification accuracy.

Abstract

We introduce a novel dataset consisting of images depicting pink eggs that have been identified as Pomacea canaliculata eggs, accompanied by corresponding bounding box annotations. The purpose of this dataset is to aid researchers in the analysis of the spread of Pomacea canaliculata species by utilizing deep learning techniques, as well as supporting other investigative pursuits that require visual data pertaining to the eggs of Pomacea canaliculata. It is worth noting, however, that the identity of the eggs in question is not definitively established, as other species within the same taxonomic family have been observed to lay similar-looking eggs in regions of the Americas. Therefore, a crucial prerequisite to any decision regarding the elimination of these eggs would be to establish with certainty whether they are exclusively attributable to invasive Pomacea canaliculata or if other species are also involved. The dataset is available at https://www.kaggle.com/datasets/deeshenzhen/pinkeggs