Datasets for training and validating a deep learning-based system to detect microfossil fish teeth from slide images

In this paper, we describe the three datasets that were used to train, validate, and test deep learning models to detect mi-crofossil fish teeth. The first dataset was created for train-ing and validating a Mask R-CNN model to detect fish teeth in the images taken using the microscope. The training set contained 866 images and one annotation file; the validation set contained 92 images and one annotation file. The second dataset was created for training and validating EfficientNet-V2 models; it included 17,400 images of teeth and 15,036 images that contained only noise (particles other than teeth). The third dataset was created to evaluate the performance of a system that combines a Mask R-CNN model and an EfficientNet-V2 model; it contained 5177 images with anno-tation files for the locations of 431 teeth within the images.(c) 2023 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY license ( http://creativecommons.org/licenses/by/4.0/ )