Dataset for varroa mite detection on sticky boards

  1. Divasón, Jose 1
  2. Romero, Ana 1
  3. Martínez de Pisón, Francisco Javier 1
  4. Silvestre, Miguel A. 2
  5. Santolaria, Pilar 3
  6. Yániz, Jesús L. 3
  1. 1 Universidad de La Rioja
    info

    Universidad de La Rioja

    Logroño, España

    ROR https://ror.org/0553yr311

  2. 2 Universitat de València
    info

    Universitat de València

    Valencia, España

    ROR https://ror.org/043nxc105

  3. 3 Universidad de Zaragoza
    info

    Universidad de Zaragoza

    Zaragoza, España

    ROR https://ror.org/012a91z28

Show affiliations +

Publisher: Zenodo

Year of publication: 2023

Type: Dataset

beta Ver similares en nube de resultados
DOI: 10.5281/ZENODO.10231844 GOOGLE SCHOLAR lock_openOpen access editor

Abstract

This Zenodo entry contains several supplementary files to the paper "Analysis of Varroa mite colony infestation level using new open software based on deep learning techniques" by Jose Divasón, Ana Romero, Francisco Javier Martínez de Pisón, Miguel A. Silvestre, Pilar Santolaria and Jesús L. Yániz. The code is also publicly available in Github: https://github.com/jodivaso/varroa_detector The following files are included in this entry: dataset.zip: this file contains the dataset that consists of 64 images (dimensions 8064 x 6048) of sticky boards with varroa mites. The compressed file also includes the labels (the annotations). images_deblurGAN.zip: this file contains the same 64 images, but after applying deblurGAN techniques. df_dataset.csv: CSV containing the information which images belong to the training set and which belong to the validation set. models.zip: it contains the different deep learning models that have been developed. example.zip: compressed file that includes a model (based on Faster R-CNN with resnet18 as backbone and fpn) and one image.